xlm-roBERTa-large-tass – AI Model by judajaav | AlphaNeural AI

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judajaav/
xlm-roBERTa-large-tass

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-large

text-embeddings-inference

endpoints_compatible

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results

This model is a fine-tuned version of xlm-roberta-large on the Tass dataset. It achieves the following results on the evaluation set:

Loss: 0.8187
Accuracy: 0.6848
F1: 0.6754

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: 1e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.8864	1.0	300	0.9594	0.4893	0.3957
0.7847	2.0	600	0.7880	0.6525	0.6432
0.6791	3.0	900	0.7441	0.6709	0.6646
0.5428	4.0	1200	0.8187	0.6848	0.6754
0.3746	5.0	1500	0.9587	0.6807	0.6729
0.3164	6.0	1800	1.0413	0.6713	0.6685

Framework versions

Transformers 4.56.1
Pytorch 2.10.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2