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XLM-RoBERTa-xtreme-en-token-drift – AI Model by arize-ai | AlphaNeural AI
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XLM-RoBERTa-xtreme-en-token-drift
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transformers
pytorch
tensorboard
xlm-roberta
token-classification
generated_from_trainer
xtreme_en_token_drift
mit
model-index
autotrain_compatible
endpoints_compatible
us
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XLM-RoBERTa-xtreme-en-token-drift
This model is a fine-tuned version of
xlm-roberta-base
on the xtreme_en_token_drift dataset. It achieves the following results on the evaluation set:
Loss: 0.2802
Accuracy: 0.9089
F1: 0.7613
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: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
0.6398
1.0
161
0.3421
0.8973
0.7111
0.3268
2.0
322
0.2846
0.9097
0.7611
0.2701
3.0
483
0.2802
0.9089
0.7613
Framework versions
Transformers 4.20.1
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1
