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roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli-strategy3-fold-2 – AI Model by sercetexam9 | AlphaNeural AI
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roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli-strategy3-fold-2
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transformers
safetensors
roberta
text-classification
generated_from_trainer
ynie/roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli
finetune
mit
text-embeddings-inference
endpoints_compatible
us
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roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli-strategy3-fold-2
This model is a fine-tuned version of
ynie/roberta-large-snli_mnli_fever_anli_R1_R2_R3-nli
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5869
Accuracy: 0.8044
F1 Macro: 0.8046
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: 2
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 8
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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1 Macro
0.6138
1.0
383
0.5715
0.7953
0.7957
0.4328
2.0
766
0.5869
0.8044
0.8046
Framework versions
Transformers 4.56.2
Pytorch 2.8.0+cu128
Datasets 4.1.1
Tokenizers 0.22.1
