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---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: MammoLLM2
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. -->
# MammoLLM2
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6666
## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.7888 | 1.24 | 500 | 1.0984 |
| 1.1179 | 2.49 | 1000 | 1.0209 |
| 1.0556 | 3.73 | 1500 | 0.9913 |
| 1.01 | 4.98 | 2000 | 0.9653 |
| 0.9723 | 6.22 | 2500 | 0.9608 |
| 0.9425 | 7.47 | 3000 | 0.9455 |
| 0.9149 | 8.71 | 3500 | 0.9391 |
| 0.8877 | 9.96 | 4000 | 0.9253 |
| 0.8478 | 11.2 | 4500 | 0.9317 |
| 0.8142 | 12.45 | 5000 | 0.9313 |
| 0.7814 | 13.69 | 5500 | 0.9299 |
| 0.7494 | 14.93 | 6000 | 0.9330 |
| 0.7071 | 16.18 | 6500 | 0.9588 |
| 0.6774 | 17.42 | 7000 | 0.9704 |
| 0.6511 | 18.67 | 7500 | 0.9828 |
| 0.6275 | 19.91 | 8000 | 1.0007 |
| 0.595 | 21.16 | 8500 | 1.0432 |
| 0.5698 | 22.4 | 9000 | 1.0641 |
| 0.546 | 23.65 | 9500 | 1.0879 |
| 0.523 | 24.89 | 10000 | 1.0982 |
| 0.4913 | 26.14 | 10500 | 1.1579 |
| 0.4622 | 27.38 | 11000 | 1.1923 |
| 0.4378 | 28.62 | 11500 | 1.2152 |
| 0.4131 | 29.87 | 12000 | 1.2440 |
| 0.3846 | 31.11 | 12500 | 1.3181 |
| 0.3592 | 32.36 | 13000 | 1.3497 |
| 0.3411 | 33.6 | 13500 | 1.3847 |
| 0.324 | 34.85 | 14000 | 1.4070 |
| 0.3061 | 36.09 | 14500 | 1.4755 |
| 0.2903 | 37.34 | 15000 | 1.5078 |
| 0.2795 | 38.58 | 15500 | 1.5351 |
| 0.2701 | 39.83 | 16000 | 1.5639 |
| 0.2605 | 41.07 | 16500 | 1.5972 |
| 0.2521 | 42.31 | 17000 | 1.6191 |
| 0.2467 | 43.56 | 17500 | 1.6300 |
| 0.2425 | 44.8 | 18000 | 1.6453 |
| 0.2386 | 46.05 | 18500 | 1.6554 |
| 0.2356 | 47.29 | 19000 | 1.6628 |
| 0.2344 | 48.54 | 19500 | 1.6663 |
| 0.2333 | 49.78 | 20000 | 1.6666 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.3
- Tokenizers 0.13.3
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