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trainer_output

Text Classification
Transformers
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +14 -9
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2282
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- - Accuracy: 0.8994
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - distributed_type: multi-GPU
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 30 | 0.3275 | 0.8742 |
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- | No log | 2.0 | 60 | 0.2814 | 0.8742 |
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- | No log | 3.0 | 90 | 0.2618 | 0.8868 |
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- | No log | 4.0 | 120 | 0.2430 | 0.8868 |
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- | No log | 5.0 | 150 | 0.2282 | 0.8994 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2474
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+ - Accuracy: 0.8742
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - distributed_type: multi-GPU
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 30 | 0.2506 | 0.8931 |
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+ | No log | 2.0 | 60 | 0.2735 | 0.8931 |
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+ | No log | 3.0 | 90 | 0.2605 | 0.8805 |
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+ | No log | 4.0 | 120 | 0.2547 | 0.8805 |
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+ | No log | 5.0 | 150 | 0.2502 | 0.8805 |
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+ | No log | 6.0 | 180 | 0.2590 | 0.8931 |
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+ | No log | 7.0 | 210 | 0.2370 | 0.8805 |
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+ | No log | 8.0 | 240 | 0.2344 | 0.9245 |
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+ | No log | 9.0 | 270 | 0.2500 | 0.8805 |
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+ | No log | 10.0 | 300 | 0.2474 | 0.8742 |
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  ### Framework versions
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