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multilingual_model – AI Model by Yashaswini21 | AlphaNeural AI
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Yashaswini21
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multilingual_model
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transformers
tensorboard
safetensors
xlm-roberta
text-classification
generated_from_trainer
Yashaswini21/multilingual_model
finetune
mit
autotrain_compatible
endpoints_compatible
us
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multilingual_model
This model is a fine-tuned version of
Yashaswini21/multilingual_model
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2701
Accuracy: 0.8973
Precision: 0.9086
Recall: 0.9136
F1: 0.9111
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: 32
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
Precision
Recall
F1
0.2869
1.0
11097
0.2899
0.8771
0.8760
0.9163
0.8957
0.2671
2.0
22194
0.2765
0.8938
0.9042
0.9122
0.9082
0.1957
3.0
33291
0.2701
0.8973
0.9086
0.9136
0.9111
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
