
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# t5-small-finetuned-text2log-compute-metrics-v5-400

This model is a fine-tuned version of [mrm8488/t5-small-finetuned-text2log](https://huggingface.co/mrm8488/t5-small-finetuned-text2log) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5820
- Bleu: 30.1378
- Gen Len: 18.568

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 23   | 1.5732          | 8.4784  | 17.3373 |
| No log        | 2.0   | 46   | 1.1400          | 22.8492 | 18.8284 |
| No log        | 3.0   | 69   | 0.9426          | 27.2247 | 18.787  |
| No log        | 4.0   | 92   | 0.8110          | 26.0131 | 18.7101 |
| No log        | 5.0   | 115  | 0.7559          | 24.1316 | 18.7988 |
| No log        | 6.0   | 138  | 0.7102          | 25.4664 | 18.7692 |
| No log        | 7.0   | 161  | 0.6807          | 26.2651 | 18.6923 |
| No log        | 8.0   | 184  | 0.6575          | 27.5298 | 18.6213 |
| No log        | 9.0   | 207  | 0.6369          | 28.8178 | 18.5976 |
| No log        | 10.0  | 230  | 0.6250          | 27.2363 | 18.6864 |
| No log        | 11.0  | 253  | 0.6143          | 28.7917 | 18.6391 |
| No log        | 12.0  | 276  | 0.5973          | 29.6901 | 18.7041 |
| No log        | 13.0  | 299  | 0.5864          | 29.6632 | 18.6568 |
| No log        | 14.0  | 322  | 0.5827          | 29.874  | 18.6391 |
| No log        | 15.0  | 345  | 0.5700          | 29.6188 | 18.6864 |
| No log        | 16.0  | 368  | 0.5620          | 29.9895 | 18.7278 |
| No log        | 17.0  | 391  | 0.5569          | 29.3883 | 18.7278 |
| No log        | 18.0  | 414  | 0.5486          | 29.783  | 18.6864 |
| No log        | 19.0  | 437  | 0.5520          | 29.4199 | 18.6568 |
| No log        | 20.0  | 460  | 0.5496          | 28.8502 | 18.6923 |
| No log        | 21.0  | 483  | 0.5495          | 29.2369 | 18.7337 |
| 0.8287        | 22.0  | 506  | 0.5411          | 29.1707 | 18.6923 |
| 0.8287        | 23.0  | 529  | 0.5325          | 28.8466 | 18.6923 |
| 0.8287        | 24.0  | 552  | 0.5388          | 29.2703 | 18.6746 |
| 0.8287        | 25.0  | 575  | 0.5288          | 28.7683 | 18.7278 |
| 0.8287        | 26.0  | 598  | 0.5299          | 28.3489 | 18.7337 |
| 0.8287        | 27.0  | 621  | 0.5314          | 28.2042 | 18.7278 |
| 0.8287        | 28.0  | 644  | 0.5159          | 29.5603 | 18.7574 |
| 0.8287        | 29.0  | 667  | 0.5163          | 28.8959 | 18.6982 |
| 0.8287        | 30.0  | 690  | 0.5170          | 30.0671 | 18.7219 |
| 0.8287        | 31.0  | 713  | 0.5202          | 28.9559 | 18.6686 |
| 0.8287        | 32.0  | 736  | 0.5181          | 28.1951 | 18.7574 |
| 0.8287        | 33.0  | 759  | 0.5134          | 28.2097 | 18.7041 |
| 0.8287        | 34.0  | 782  | 0.5134          | 28.0953 | 18.7574 |
| 0.8287        | 35.0  | 805  | 0.5165          | 28.4171 | 18.7988 |
| 0.8287        | 36.0  | 828  | 0.5195          | 28.7953 | 18.7633 |
| 0.8287        | 37.0  | 851  | 0.5185          | 29.1606 | 18.7633 |
| 0.8287        | 38.0  | 874  | 0.5192          | 29.5226 | 18.6805 |
| 0.8287        | 39.0  | 897  | 0.5178          | 28.425  | 18.7692 |
| 0.8287        | 40.0  | 920  | 0.5196          | 29.4795 | 18.7041 |
| 0.8287        | 41.0  | 943  | 0.5161          | 29.5127 | 18.7041 |
| 0.8287        | 42.0  | 966  | 0.5164          | 28.6225 | 18.7574 |
| 0.8287        | 43.0  | 989  | 0.5183          | 29.0629 | 18.6272 |
| 0.3866        | 44.0  | 1012 | 0.5174          | 28.6628 | 18.6213 |
| 0.3866        | 45.0  | 1035 | 0.5141          | 28.499  | 18.6213 |
| 0.3866        | 46.0  | 1058 | 0.5151          | 28.1309 | 18.6272 |
| 0.3866        | 47.0  | 1081 | 0.5167          | 29.8871 | 18.6391 |
| 0.3866        | 48.0  | 1104 | 0.5133          | 28.7513 | 18.6331 |
| 0.3866        | 49.0  | 1127 | 0.5188          | 28.3089 | 18.6213 |
| 0.3866        | 50.0  | 1150 | 0.5203          | 28.8714 | 18.6331 |
| 0.3866        | 51.0  | 1173 | 0.5263          | 28.7644 | 18.6331 |
| 0.3866        | 52.0  | 1196 | 0.5222          | 28.4817 | 18.6331 |
| 0.3866        | 53.0  | 1219 | 0.5307          | 28.8117 | 18.6272 |
| 0.3866        | 54.0  | 1242 | 0.5255          | 29.3844 | 18.6213 |
| 0.3866        | 55.0  | 1265 | 0.5264          | 29.7108 | 18.6213 |
| 0.3866        | 56.0  | 1288 | 0.5272          | 29.353  | 18.6331 |
| 0.3866        | 57.0  | 1311 | 0.5283          | 28.5792 | 18.6391 |
| 0.3866        | 58.0  | 1334 | 0.5301          | 29.9914 | 18.6272 |
| 0.3866        | 59.0  | 1357 | 0.5320          | 29.3162 | 18.6272 |
| 0.3866        | 60.0  | 1380 | 0.5380          | 29.2162 | 18.6272 |
| 0.3866        | 61.0  | 1403 | 0.5349          | 28.5292 | 18.6272 |
| 0.3866        | 62.0  | 1426 | 0.5313          | 28.7165 | 18.6627 |
| 0.3866        | 63.0  | 1449 | 0.5335          | 29.3637 | 18.6154 |
| 0.3866        | 64.0  | 1472 | 0.5350          | 29.3612 | 18.568  |
| 0.3866        | 65.0  | 1495 | 0.5330          | 29.1338 | 18.5621 |
| 0.283         | 66.0  | 1518 | 0.5322          | 29.0514 | 18.5562 |
| 0.283         | 67.0  | 1541 | 0.5362          | 29.2592 | 18.5562 |
| 0.283         | 68.0  | 1564 | 0.5379          | 29.6757 | 18.568  |
| 0.283         | 69.0  | 1587 | 0.5386          | 29.5012 | 18.5976 |
| 0.283         | 70.0  | 1610 | 0.5379          | 29.6616 | 18.5917 |
| 0.283         | 71.0  | 1633 | 0.5364          | 29.8762 | 18.6154 |
| 0.283         | 72.0  | 1656 | 0.5392          | 29.7143 | 18.6036 |
| 0.283         | 73.0  | 1679 | 0.5438          | 29.385  | 18.5976 |
| 0.283         | 74.0  | 1702 | 0.5386          | 28.3472 | 18.6095 |
| 0.283         | 75.0  | 1725 | 0.5372          | 29.1045 | 18.574  |
| 0.283         | 76.0  | 1748 | 0.5406          | 29.0839 | 18.6095 |
| 0.283         | 77.0  | 1771 | 0.5408          | 29.735  | 18.5799 |
| 0.283         | 78.0  | 1794 | 0.5406          | 29.5432 | 18.6036 |
| 0.283         | 79.0  | 1817 | 0.5413          | 29.1501 | 18.5976 |
| 0.283         | 80.0  | 1840 | 0.5434          | 29.5822 | 18.6095 |
| 0.283         | 81.0  | 1863 | 0.5491          | 29.1933 | 18.5799 |
| 0.283         | 82.0  | 1886 | 0.5473          | 28.9065 | 18.5385 |
| 0.283         | 83.0  | 1909 | 0.5507          | 29.4129 | 18.5385 |
| 0.283         | 84.0  | 1932 | 0.5534          | 29.2249 | 18.5385 |
| 0.283         | 85.0  | 1955 | 0.5561          | 29.6955 | 18.5799 |
| 0.283         | 86.0  | 1978 | 0.5575          | 29.1081 | 18.5385 |
| 0.2296        | 87.0  | 2001 | 0.5531          | 29.7633 | 18.5385 |
| 0.2296        | 88.0  | 2024 | 0.5548          | 30.045  | 18.5385 |
| 0.2296        | 89.0  | 2047 | 0.5567          | 29.9209 | 18.5385 |
| 0.2296        | 90.0  | 2070 | 0.5577          | 29.1879 | 18.5858 |
| 0.2296        | 91.0  | 2093 | 0.5602          | 29.1587 | 18.5799 |
| 0.2296        | 92.0  | 2116 | 0.5595          | 29.5205 | 18.5799 |
| 0.2296        | 93.0  | 2139 | 0.5605          | 29.3439 | 18.5325 |
| 0.2296        | 94.0  | 2162 | 0.5583          | 29.4742 | 18.5325 |
| 0.2296        | 95.0  | 2185 | 0.5576          | 29.132  | 18.5325 |
| 0.2296        | 96.0  | 2208 | 0.5566          | 29.0861 | 18.5325 |
| 0.2296        | 97.0  | 2231 | 0.5584          | 29.6618 | 18.5385 |
| 0.2296        | 98.0  | 2254 | 0.5593          | 29.1068 | 18.5325 |
| 0.2296        | 99.0  | 2277 | 0.5603          | 29.7081 | 18.5385 |
| 0.2296        | 100.0 | 2300 | 0.5599          | 29.6368 | 18.5325 |
| 0.2296        | 101.0 | 2323 | 0.5598          | 29.6263 | 18.5325 |
| 0.2296        | 102.0 | 2346 | 0.5637          | 29.6321 | 18.5385 |
| 0.2296        | 103.0 | 2369 | 0.5678          | 29.6306 | 18.5266 |
| 0.2296        | 104.0 | 2392 | 0.5685          | 29.3279 | 18.5325 |
| 0.2296        | 105.0 | 2415 | 0.5680          | 29.1363 | 18.5621 |
| 0.2296        | 106.0 | 2438 | 0.5726          | 29.2666 | 18.5385 |
| 0.2296        | 107.0 | 2461 | 0.5738          | 29.2981 | 18.5385 |
| 0.2296        | 108.0 | 2484 | 0.5740          | 29.5752 | 18.5385 |
| 0.1942        | 109.0 | 2507 | 0.5749          | 29.5596 | 18.5385 |
| 0.1942        | 110.0 | 2530 | 0.5732          | 29.6728 | 18.574  |
| 0.1942        | 111.0 | 2553 | 0.5738          | 29.6052 | 18.5325 |
| 0.1942        | 112.0 | 2576 | 0.5731          | 29.5143 | 18.574  |
| 0.1942        | 113.0 | 2599 | 0.5744          | 29.8059 | 18.574  |
| 0.1942        | 114.0 | 2622 | 0.5751          | 29.6796 | 18.574  |
| 0.1942        | 115.0 | 2645 | 0.5763          | 29.9279 | 18.568  |
| 0.1942        | 116.0 | 2668 | 0.5746          | 29.892  | 18.568  |
| 0.1942        | 117.0 | 2691 | 0.5741          | 29.8104 | 18.574  |
| 0.1942        | 118.0 | 2714 | 0.5759          | 29.6379 | 18.574  |
| 0.1942        | 119.0 | 2737 | 0.5777          | 29.7949 | 18.574  |
| 0.1942        | 120.0 | 2760 | 0.5776          | 29.6297 | 18.574  |
| 0.1942        | 121.0 | 2783 | 0.5789          | 29.5298 | 18.574  |
| 0.1942        | 122.0 | 2806 | 0.5794          | 29.6102 | 18.574  |
| 0.1942        | 123.0 | 2829 | 0.5799          | 29.7981 | 18.574  |
| 0.1942        | 124.0 | 2852 | 0.5811          | 30.0894 | 18.574  |
| 0.1942        | 125.0 | 2875 | 0.5826          | 29.9849 | 18.574  |
| 0.1942        | 126.0 | 2898 | 0.5829          | 29.8349 | 18.574  |
| 0.1942        | 127.0 | 2921 | 0.5817          | 29.6295 | 18.574  |
| 0.1942        | 128.0 | 2944 | 0.5809          | 29.5264 | 18.568  |
| 0.1942        | 129.0 | 2967 | 0.5813          | 29.5858 | 18.568  |
| 0.1942        | 130.0 | 2990 | 0.5843          | 29.6556 | 18.568  |
| 0.1777        | 131.0 | 3013 | 0.5836          | 30.0165 | 18.568  |
| 0.1777        | 132.0 | 3036 | 0.5835          | 29.8399 | 18.568  |
| 0.1777        | 133.0 | 3059 | 0.5824          | 29.8065 | 18.568  |
| 0.1777        | 134.0 | 3082 | 0.5821          | 29.8948 | 18.574  |
| 0.1777        | 135.0 | 3105 | 0.5808          | 29.9342 | 18.574  |
| 0.1777        | 136.0 | 3128 | 0.5810          | 29.7556 | 18.574  |
| 0.1777        | 137.0 | 3151 | 0.5813          | 30.0425 | 18.568  |
| 0.1777        | 138.0 | 3174 | 0.5822          | 30.0719 | 18.568  |
| 0.1777        | 139.0 | 3197 | 0.5823          | 30.0719 | 18.568  |
| 0.1777        | 140.0 | 3220 | 0.5828          | 30.1124 | 18.568  |
| 0.1777        | 141.0 | 3243 | 0.5826          | 30.1451 | 18.568  |
| 0.1777        | 142.0 | 3266 | 0.5828          | 30.1451 | 18.568  |
| 0.1777        | 143.0 | 3289 | 0.5829          | 30.1451 | 18.568  |
| 0.1777        | 144.0 | 3312 | 0.5829          | 30.1451 | 18.568  |
| 0.1777        | 145.0 | 3335 | 0.5825          | 30.1378 | 18.568  |
| 0.1777        | 146.0 | 3358 | 0.5824          | 30.1378 | 18.568  |
| 0.1777        | 147.0 | 3381 | 0.5822          | 30.1378 | 18.568  |
| 0.1777        | 148.0 | 3404 | 0.5820          | 30.1378 | 18.568  |
| 0.1777        | 149.0 | 3427 | 0.5821          | 30.1378 | 18.568  |
| 0.1777        | 150.0 | 3450 | 0.5820          | 30.1378 | 18.568  |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "t5-small-finetuned-text2log-compute-metrics-v5-400", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-finetuned-text2log-compute-metrics-v5-400
==================================================


This model is a fine-tuned version of mrm8488/t5-small-finetuned-text2log on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5820
* Bleu: 30.1378
* Gen Len: 18.568


Model description
-----------------


More information needed


Intended uses & limitations
---------------------------


More information needed


Training and evaluation data
----------------------------


More information needed


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 150
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1