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# t5-small_6_3-en-hi_en_bt

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9293
- Bleu: 8.9676
- Gen Len: 33.391

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 3.7929        | 1.0   | 526   | 2.6759          | 1.5672 | 16.749  |
| 3.1151        | 2.0   | 1052  | 2.3843          | 2.2962 | 16.5287 |
| 2.8701        | 3.0   | 1578  | 2.2287          | 2.8811 | 16.4953 |
| 2.7121        | 4.0   | 2104  | 2.1302          | 3.3949 | 16.5247 |
| 2.5844        | 5.0   | 2630  | 2.0593          | 3.8161 | 16.4513 |
| 2.4917        | 6.0   | 3156  | 2.0063          | 3.9831 | 16.4272 |
| 2.4067        | 7.0   | 3682  | 1.9733          | 4.0511 | 16.3378 |
| 2.3395        | 8.0   | 4208  | 1.9399          | 4.3067 | 16.4112 |
| 2.2713        | 9.0   | 4734  | 1.9148          | 4.3195 | 16.3618 |
| 2.2217        | 10.0  | 5260  | 1.8961          | 4.3905 | 16.4112 |
| 2.1659        | 11.0  | 5786  | 1.8787          | 4.4548 | 16.3298 |
| 2.1267        | 12.0  | 6312  | 1.8651          | 4.5779 | 16.3618 |
| 2.0793        | 13.0  | 6838  | 1.8540          | 4.4863 | 16.2603 |
| 2.0473        | 14.0  | 7364  | 1.8444          | 4.556  | 16.3044 |
| 2.0082        | 15.0  | 7890  | 1.8353          | 4.5957 | 16.3124 |
| 1.9748        | 16.0  | 8416  | 1.8313          | 4.5593 | 16.3204 |
| 1.9456        | 17.0  | 8942  | 1.8259          | 4.4522 | 16.2764 |
| 1.9177        | 18.0  | 9468  | 1.8231          | 4.3345 | 16.3084 |
| 1.8871        | 19.0  | 9994  | 1.8177          | 4.48   | 16.3458 |
| 1.8422        | 20.0  | 10520 | 1.8123          | 4.5078 | 16.287  |
| 1.8161        | 21.0  | 11046 | 1.8106          | 4.3289 | 16.3405 |
| 1.7972        | 22.0  | 11572 | 1.8106          | 4.5204 | 16.3244 |
| 1.7785        | 23.0  | 12098 | 1.8117          | 4.4651 | 16.3605 |
| 1.7563        | 24.0  | 12624 | 1.8125          | 4.3938 | 16.3538 |
| 1.7444        | 25.0  | 13150 | 1.8089          | 4.5367 | 16.3792 |
| 1.7256        | 26.0  | 13676 | 1.8075          | 4.4212 | 16.3925 |
| 1.7021        | 27.0  | 14202 | 1.8080          | 4.5491 | 16.3992 |
| 1.6969        | 28.0  | 14728 | 1.8061          | 4.6568 | 16.3645 |
| 1.6766        | 29.0  | 15254 | 1.8063          | 4.6297 | 16.3738 |
| 1.6653        | 30.0  | 15780 | 1.8095          | 4.6167 | 16.2977 |
| 1.6543        | 31.0  | 16306 | 1.8085          | 4.5452 | 16.3538 |
| 1.6413        | 32.0  | 16832 | 1.8112          | 4.6667 | 16.3351 |
| 1.6293        | 33.0  | 17358 | 1.8126          | 4.6127 | 16.3351 |
| 1.6204        | 34.0  | 17884 | 1.8115          | 4.7196 | 16.3111 |
| 1.6082        | 35.0  | 18410 | 1.8134          | 4.7011 | 16.3324 |
| 1.6048        | 36.0  | 18936 | 1.8122          | 4.6429 | 16.2964 |
| 1.5911        | 37.0  | 19462 | 1.8143          | 4.6424 | 16.3124 |
| 1.5834        | 38.0  | 19988 | 1.8131          | 4.6254 | 16.3164 |
| 1.5742        | 39.0  | 20514 | 1.8154          | 4.6998 | 16.287  |
| 1.5623        | 40.0  | 21040 | 1.8147          | 4.6469 | 16.3471 |
| 1.5599        | 41.0  | 21566 | 1.8185          | 4.6654 | 16.3231 |
| 1.5516        | 42.0  | 22092 | 1.8173          | 4.6961 | 16.3471 |
| 1.5441        | 43.0  | 22618 | 1.8180          | 4.7176 | 16.3084 |
| 1.545         | 44.0  | 23144 | 1.8177          | 4.5571 | 16.275  |
| 1.5418        | 45.0  | 23670 | 1.8195          | 4.5927 | 16.3097 |
| 1.5329        | 46.0  | 24196 | 1.8187          | 4.7025 | 16.2724 |
| 1.5348        | 47.0  | 24722 | 1.8198          | 4.6575 | 16.3057 |
| 1.5362        | 48.0  | 25248 | 1.8197          | 4.6912 | 16.2991 |
| 1.5231        | 49.0  | 25774 | 1.8202          | 4.6752 | 16.2951 |
| 1.5314        | 50.0  | 26300 | 1.8208          | 4.6114 | 16.2937 |


### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.8.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["translation", "generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "t5-small_6_3-en-hi_en_bt", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation translation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #translation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small\_6\_3-en-hi\_en\_bt
============================


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.9293
* Bleu: 8.9676
* Gen Len: 33.391


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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #translation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #translation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.8.0
* Datasets 2.1.0
* Tokenizers 0.12.1