distilcamembert-base-finetuned-allocine
This model is a fine-tuned version of cmarkea/distilcamembert-base on the allocine dataset. It achieves the following results on the evaluation set:
- Loss: 2.1493
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: 2e-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: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.4479 | 1.0 | 157 | 2.2066 |
2.3065 | 2.0 | 314 | 2.1144 |
2.2567 | 3.0 | 471 | 2.1565 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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