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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: gpt-m-large
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. -->
# gpt-m-large
This model is a fine-tuned version of [augustocsc/gpt-m-large](https://huggingface.co/augustocsc/gpt-m-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0327
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.0343 | 0.03 | 1000 | 0.0343 |
| 0.0337 | 0.06 | 2000 | 0.0342 |
| 0.0338 | 0.09 | 3000 | 0.0338 |
| 0.0349 | 0.13 | 4000 | 0.0337 |
| 0.034 | 0.16 | 5000 | 0.0335 |
| 0.0342 | 0.19 | 6000 | 0.0334 |
| 0.0341 | 0.22 | 7000 | 0.0333 |
| 0.0339 | 0.25 | 8000 | 0.0333 |
| 0.0336 | 0.28 | 9000 | 0.0331 |
| 0.0335 | 0.31 | 10000 | 0.0330 |
| 0.0334 | 0.35 | 11000 | 0.0330 |
| 0.0331 | 0.38 | 12000 | 0.0328 |
| 0.0332 | 0.41 | 13000 | 0.0328 |
| 0.0327 | 0.44 | 14000 | 0.0327 |
| 0.0331 | 0.47 | 15000 | 0.0327 |
| 0.0335 | 0.5 | 16000 | 0.0327 |
| 0.0333 | 0.53 | 17000 | 0.0327 |
| 0.0333 | 0.57 | 18000 | 0.0327 |
| 0.0333 | 0.6 | 19000 | 0.0327 |
| 0.0332 | 0.63 | 20000 | 0.0327 |
| 0.0331 | 0.66 | 21000 | 0.0327 |
| 0.0328 | 0.69 | 22000 | 0.0327 |
| 0.033 | 0.72 | 23000 | 0.0327 |
| 0.0334 | 0.75 | 24000 | 0.0327 |
| 0.0334 | 0.79 | 25000 | 0.0327 |
| 0.0333 | 0.82 | 26000 | 0.0327 |
| 0.0332 | 0.85 | 27000 | 0.0327 |
| 0.033 | 0.88 | 28000 | 0.0327 |
| 0.033 | 0.91 | 29000 | 0.0327 |
| 0.0331 | 0.94 | 30000 | 0.0327 |
| 0.0335 | 0.97 | 31000 | 0.0327 |
### Framework versions
- Transformers 4.27.3
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
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