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gpt2-concat-cbt-rarity-all-7k-p8k
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 3.1838
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
6.7249 | 0.29 | 500 | 5.6400 |
5.3729 | 0.59 | 1000 | 5.2003 |
5.0283 | 0.88 | 1500 | 4.9502 |
4.7537 | 1.17 | 2000 | 4.8035 |
4.5903 | 1.47 | 2500 | 4.6765 |
4.4832 | 1.76 | 3000 | 4.5717 |
4.3484 | 2.05 | 3500 | 4.4930 |
4.1512 | 2.35 | 4000 | 4.4467 |
4.1329 | 2.64 | 4500 | 4.3805 |
4.091 | 2.93 | 5000 | 4.3309 |
3.8799 | 3.23 | 5500 | 4.3273 |
3.8248 | 3.52 | 6000 | 4.2923 |
3.8074 | 3.81 | 6500 | 4.2605 |
3.6914 | 4.11 | 7000 | 4.2581 |
3.534 | 4.4 | 7500 | 4.2538 |
3.5261 | 4.69 | 8000 | 4.2382 |
3.5255 | 4.99 | 8500 | 4.2256 |
3.351 | 5.28 | 9000 | 4.2383 |
3.3357 | 5.57 | 9500 | 4.2375 |
3.3375 | 5.87 | 10000 | 4.2364 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3