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e5_RSE_v2 – AI Model by Ludo33 | AlphaNeural AI
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Ludo33
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e5_RSE_v2
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transformers
safetensors
xlm-roberta
text-classification
generated_from_trainer
intfloat/multilingual-e5-large-instruct
finetune
mit
autotrain_compatible
endpoints_compatible
us
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e5_RSE_v2
This model is a fine-tuned version of
intfloat/multilingual-e5-large-instruct
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3621
Accuracy: 0.9074
F1: 0.9059
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 20
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
2.0336
1.0
69
1.0876
0.7332
0.7067
1.0637
2.0
138
0.3396
0.8757
0.8747
0.2544
3.0
207
0.3081
0.9047
0.9035
0.1172
4.0
276
0.3542
0.9056
0.9047
0.0868
5.0
345
0.3621
0.9074
0.9059
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
