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---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: 4_bar_lmd_clean_custom_test3
  results: []
---

<!-- 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. -->

# 4_bar_lmd_clean_custom_test3

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4912

## 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: 0.005
- train_batch_size: 48
- eval_batch_size: 32
- seed: 1
- gradient_accumulation_steps: 2
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.8709        | 1.82  | 10   | 5.7363          |
| 5.6849        | 3.64  | 20   | 5.4321          |
| 5.4501        | 5.45  | 30   | 5.3610          |
| 5.359         | 7.27  | 40   | 5.2833          |
| 5.278         | 9.09  | 50   | 5.1274          |
| 5.1335        | 10.91 | 60   | 5.0075          |
| 5.0548        | 12.73 | 70   | 4.9488          |
| 4.958         | 14.55 | 80   | 4.8213          |
| 4.8511        | 16.36 | 90   | 4.7643          |
| 4.8158        | 18.18 | 100  | 4.7202          |
| 4.7548        | 20.0  | 110  | 4.6591          |
| 4.7269        | 21.82 | 120  | 4.6380          |
| 4.6823        | 23.64 | 130  | 4.6200          |
| 4.6757        | 25.45 | 140  | 4.6081          |
| 4.629         | 27.27 | 150  | 4.6285          |
| 4.6398        | 29.09 | 160  | 4.6024          |
| 4.6111        | 30.91 | 170  | 4.6235          |
| 4.6028        | 32.73 | 180  | 4.5945          |
| 4.577         | 34.55 | 190  | 4.5932          |
| 4.5812        | 36.36 | 200  | 4.5689          |
| 4.5583        | 38.18 | 210  | 4.5713          |
| 4.5567        | 40.0  | 220  | 4.5731          |
| 4.55          | 41.82 | 230  | 4.5619          |
| 4.5338        | 43.64 | 240  | 4.5656          |
| 4.5245        | 45.45 | 250  | 4.5494          |
| 4.5143        | 47.27 | 260  | 4.5578          |
| 4.5339        | 49.09 | 270  | 4.5489          |
| 4.4948        | 50.91 | 280  | 4.5746          |
| 4.5           | 52.73 | 290  | 4.5407          |
| 4.4755        | 54.55 | 300  | 4.5448          |
| 4.4736        | 56.36 | 310  | 4.5311          |
| 4.4584        | 58.18 | 320  | 4.5279          |
| 4.465         | 60.0  | 330  | 4.5339          |
| 4.4511        | 61.82 | 340  | 4.5326          |
| 4.4408        | 63.64 | 350  | 4.5163          |
| 4.4314        | 65.45 | 360  | 4.5193          |
| 4.417         | 67.27 | 370  | 4.5161          |
| 4.424         | 69.09 | 380  | 4.5027          |
| 4.4147        | 70.91 | 390  | 4.5044          |
| 4.3938        | 72.73 | 400  | 4.5012          |
| 4.4001        | 74.55 | 410  | 4.5037          |
| 4.3821        | 76.36 | 420  | 4.5006          |
| 4.383         | 78.18 | 430  | 4.4981          |
| 4.3893        | 80.0  | 440  | 4.4942          |
| 4.3684        | 81.82 | 450  | 4.4927          |
| 4.3788        | 83.64 | 460  | 4.4933          |
| 4.3836        | 85.45 | 470  | 4.4929          |
| 4.3766        | 87.27 | 480  | 4.4917          |
| 4.3871        | 89.09 | 490  | 4.4912          |
| 4.3725        | 90.91 | 500  | 4.4912          |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.0
- Datasets 2.15.0
- Tokenizers 0.15.1