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# great-books-bot-4

This model is a fine-tuned version of [erikanesse/great-books-bot](https://huggingface.co/erikanesse/great-books-bot) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9485

## 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: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- gradient_accumulation_steps: 5
- total_train_batch_size: 5
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.8623        | 0.01  | 20   | 4.0416          |
| 3.8944        | 0.02  | 40   | 4.0495          |
| 4.0613        | 0.03  | 60   | 4.0321          |
| 3.9456        | 0.04  | 80   | 4.0543          |
| 3.9298        | 0.05  | 100  | 4.0518          |
| 3.951         | 0.06  | 120  | 4.0281          |
| 3.8512        | 0.07  | 140  | 4.0309          |
| 4.0738        | 0.08  | 160  | 4.0358          |
| 3.9713        | 0.09  | 180  | 4.0130          |
| 3.9149        | 0.1   | 200  | 4.0469          |
| 3.9674        | 0.11  | 220  | 4.0395          |
| 4.1288        | 0.12  | 240  | 4.0422          |
| 3.9388        | 0.13  | 260  | 4.0552          |
| 4.0308        | 0.14  | 280  | 4.0643          |
| 3.9006        | 0.15  | 300  | 4.0624          |
| 3.9531        | 0.16  | 320  | 4.0482          |
| 3.985         | 0.17  | 340  | 4.0538          |
| 3.8275        | 0.18  | 360  | 4.0420          |
| 3.9002        | 0.19  | 380  | 4.0525          |
| 3.8415        | 0.2   | 400  | 4.0395          |
| 3.888         | 0.21  | 420  | 4.0422          |
| 3.8562        | 0.22  | 440  | 4.0171          |
| 3.9306        | 0.23  | 460  | 4.0280          |
| 3.8681        | 0.24  | 480  | 4.0340          |
| 3.8337        | 0.25  | 500  | 4.0101          |
| 3.853         | 0.26  | 520  | 4.0334          |
| 3.9567        | 0.27  | 540  | 4.0421          |
| 3.9489        | 0.28  | 560  | 4.0390          |
| 3.9693        | 0.29  | 580  | 4.0221          |
| 4.0172        | 0.3   | 600  | 4.0040          |
| 3.8797        | 0.31  | 620  | 4.0225          |
| 3.8353        | 0.32  | 640  | 4.0177          |
| 3.7483        | 0.33  | 660  | 4.0173          |
| 3.8179        | 0.34  | 680  | 4.0037          |
| 3.8957        | 0.35  | 700  | 4.0079          |
| 3.9634        | 0.36  | 720  | 4.0300          |
| 3.8911        | 0.37  | 740  | 4.0261          |
| 3.9296        | 0.38  | 760  | 4.0224          |
| 3.9195        | 0.39  | 780  | 4.0133          |
| 3.8455        | 0.4   | 800  | 4.0061          |
| 3.7869        | 0.41  | 820  | 4.0191          |
| 3.9417        | 0.42  | 840  | 4.0198          |
| 3.8437        | 0.43  | 860  | 4.0213          |
| 3.9039        | 0.44  | 880  | 3.9977          |
| 3.9966        | 0.45  | 900  | 4.0057          |
| 3.8641        | 0.46  | 920  | 3.9954          |
| 3.9355        | 0.47  | 940  | 4.0063          |
| 3.9496        | 0.48  | 960  | 3.9946          |
| 3.9551        | 0.49  | 980  | 4.0031          |
| 3.9199        | 0.5   | 1000 | 4.0071          |
| 3.9086        | 0.51  | 1020 | 3.9915          |
| 3.8584        | 0.52  | 1040 | 4.0360          |
| 3.8317        | 0.53  | 1060 | 4.0207          |
| 3.7805        | 0.54  | 1080 | 3.9918          |
| 3.7688        | 0.55  | 1100 | 3.9961          |
| 3.7708        | 0.56  | 1120 | 3.9960          |
| 3.8142        | 0.57  | 1140 | 3.9882          |
| 3.8483        | 0.58  | 1160 | 3.9935          |
| 3.9744        | 0.59  | 1180 | 3.9856          |
| 3.7912        | 0.6   | 1200 | 3.9911          |
| 3.8575        | 0.61  | 1220 | 3.9993          |
| 3.9246        | 0.62  | 1240 | 3.9908          |
| 3.786         | 0.63  | 1260 | 3.9947          |
| 3.8222        | 0.64  | 1280 | 3.9734          |
| 3.8651        | 0.65  | 1300 | 3.9748          |
| 3.8582        | 0.66  | 1320 | 3.9598          |
| 3.8398        | 0.67  | 1340 | 3.9538          |
| 3.9176        | 0.68  | 1360 | 3.9563          |
| 3.8013        | 0.69  | 1380 | 3.9660          |
| 3.9405        | 0.7   | 1400 | 3.9716          |
| 3.9182        | 0.71  | 1420 | 3.9725          |
| 3.8787        | 0.72  | 1440 | 3.9654          |
| 3.8406        | 0.73  | 1460 | 3.9525          |
| 3.8775        | 0.74  | 1480 | 3.9601          |
| 3.845         | 0.75  | 1500 | 3.9602          |
| 3.7902        | 0.76  | 1520 | 3.9585          |
| 3.7236        | 0.77  | 1540 | 3.9643          |
| 3.7734        | 0.78  | 1560 | 3.9600          |
| 3.7393        | 0.79  | 1580 | 3.9605          |
| 3.8666        | 0.8   | 1600 | 3.9557          |
| 3.9247        | 0.81  | 1620 | 3.9596          |
| 3.7902        | 0.82  | 1640 | 3.9545          |
| 3.7469        | 0.83  | 1660 | 3.9552          |
| 3.7093        | 0.84  | 1680 | 3.9573          |
| 3.8674        | 0.85  | 1700 | 3.9568          |
| 3.8095        | 0.86  | 1720 | 3.9546          |
| 3.899         | 0.87  | 1740 | 3.9537          |
| 3.806         | 0.88  | 1760 | 3.9541          |
| 3.8183        | 0.89  | 1780 | 3.9610          |
| 3.7686        | 0.9   | 1800 | 3.9537          |
| 3.7624        | 0.91  | 1820 | 3.9535          |
| 3.8613        | 0.92  | 1840 | 3.9497          |
| 3.6526        | 0.93  | 1860 | 3.9491          |
| 3.7679        | 0.94  | 1880 | 3.9518          |
| 3.7848        | 0.95  | 1900 | 3.9523          |
| 3.7083        | 0.96  | 1920 | 3.9492          |
| 3.8315        | 0.97  | 1940 | 3.9484          |
| 3.7784        | 0.98  | 1960 | 3.9485          |
| 3.8287        | 0.99  | 1980 | 3.9484          |
| 3.8246        | 1.0   | 2000 | 3.9485          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.9.0+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "great-books-bot-4", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

great-books-bot-4
=================


This model is a fine-tuned version of erikanesse/great-books-bot on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 3.9485


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: 1
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: tpu
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 5
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.9.0+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 1
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: tpu
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 5
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.9.0+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #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: 1
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: tpu
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 5
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.9.0+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #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: 1
* eval\_batch\_size: 8
* seed: 42
* distributed\_type: tpu
* gradient\_accumulation\_steps: 5
* total\_train\_batch\_size: 5
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 2000### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.9.0+cu102
* Datasets 2.4.0
* Tokenizers 0.12.1