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moses_cbgpt
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5234
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: 0.0004
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.9833 | 0.18 | 1000 | 0.7188 |
| 0.6852 | 0.36 | 2000 | 0.6362 |
| 0.6347 | 0.54 | 3000 | 0.6076 |
| 0.6094 | 0.72 | 4000 | 0.5887 |
| 0.5908 | 0.9 | 5000 | 0.5725 |
| 0.5743 | 1.08 | 6000 | 0.5608 |
| 0.5606 | 1.26 | 7000 | 0.5483 |
| 0.5492 | 1.44 | 8000 | 0.5373 |
| 0.5396 | 1.62 | 9000 | 0.5298 |
| 0.5327 | 1.79 | 10000 | 0.5248 |
| 0.5289 | 1.97 | 11000 | 0.5234 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
