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JbKHH_xlni – AI Model by hugojordan23 | AlphaNeural AI
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transformers
safetensors
camembert
text-classification
generated_from_trainer
fr
almanach/camembert-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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camembert-base-finetuned-xnli-fr
This model is a fine-tuned version of
camembert-base
on the xnli dataset. It achieves the following results on the evaluation set:
Loss: 0.5061
Accuracy: 0.8104
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.5286
1.0
6136
0.5082
0.7908
0.4568
2.0
12272
0.5018
0.8052
0.3941
3.0
18408
0.5061
0.8104
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
