camembert_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2
This model is a fine-tuned version of camembert/camembert-base-ccnet on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0965
- Accuracy: 0.1042
- Learning Rate: 0.0008
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: 0.001
- train_batch_size: 24
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate |
---|---|---|---|---|---|
2.1119 | 1.0 | 15 | 2.1246 | 0.1042 | 0.0010 |
2.0909 | 2.0 | 30 | 2.1521 | 0.0938 | 0.0010 |
2.1043 | 3.0 | 45 | 2.0959 | 0.0938 | 0.0009 |
2.0866 | 4.0 | 60 | 2.1143 | 0.0938 | 0.0009 |
2.0746 | 5.0 | 75 | 2.1063 | 0.1354 | 0.0009 |
2.0753 | 6.0 | 90 | 2.1266 | 0.0938 | 0.0009 |
2.0793 | 7.0 | 105 | 2.1177 | 0.1146 | 0.0009 |
2.0844 | 8.0 | 120 | 2.0959 | 0.1354 | 0.0009 |
2.0855 | 9.0 | 135 | 2.1072 | 0.0938 | 0.0008 |
2.0805 | 10.0 | 150 | 2.1128 | 0.0938 | 0.0008 |
2.079 | 11.0 | 165 | 2.1027 | 0.1354 | 0.0008 |
2.0855 | 12.0 | 180 | 2.1164 | 0.0938 | 0.0008 |
2.0745 | 13.0 | 195 | 2.0965 | 0.1042 | 0.0008 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
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