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checkpoints_xnli – AI Model by PJM124 | AlphaNeural AI
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PJM124
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checkpoints_xnli
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transformers
tensorboard
safetensors
xlm-roberta
text-classification
generated_from_trainer
xnli
FacebookAI/xlm-roberta-base
finetune
mit
model-index
autotrain_compatible
endpoints_compatible
us
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checkpoints_xnli
This model is a fine-tuned version of
xlm-roberta-base
on the xnli dataset. It achieves the following results on the evaluation set:
Loss: 0.4345
Accuracy: 0.8473
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: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.4929
1.0
11045
0.4551
0.8217
0.408
2.0
22090
0.4308
0.8358
0.3093
3.0
33135
0.4345
0.8473
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
