xlm-roberta-en-raw – AI Model by emotions-entailment | AlphaNeural AI

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emotions-entailment/
xlm-roberta-en-raw

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text-classification

generated_from_trainer

emotions-entailment/zero-shot-emotions

FacebookAI/xlm-roberta-base

text-embeddings-inference

endpoints_compatible

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xlm-roberta-raw

This model is a fine-tuned version of FacebookAI/xlm-roberta-base from English data. It achieves the following results on the evaluation set:

Loss: 0.3948
F1 Micro: 0.8358
F1 Macro: 0.7817
Precision Micro: 0.8593
Recall Micro: 0.8135

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 24
eval_batch_size: 24
seed: 42
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: linear
lr_scheduler_warmup_steps: 3143
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	Precision Micro	Recall Micro
0.4010	1.0	10479	0.4013	0.8074	0.7520	0.8352	0.7813
0.4003	2.0	20958	0.3980	0.8276	0.7849	0.8391	0.8164
0.3958	3.0	31437	0.3970	0.8361	0.7937	0.8545	0.8185

Framework versions

Transformers 5.10.2
Pytorch 2.11.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2