embc25_finetuned_30000_fr_it

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embc25_finetuned_30000_fr_it

This model is a fine-tuned version of Kyungjin-Kim/mmc_roberta_500000_fr_it on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.0771
• Accuracy: 0.7732
• Precision: 0.7621
• Recall: 0.7943
• F1: 0.7779

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: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.48.1
• Pytorch 2.3.1
• Datasets 3.2.0
• Tokenizers 0.21.0