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vmw-xlm-focal – AI Model by jaycentg | AlphaNeural AI
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vmw-xlm-focal
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transformers
tensorboard
safetensors
xlm-roberta
text-classification
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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vmw-xlm-focal
This model is a fine-tuned version of
FacebookAI/xlm-roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 7.9938
F1-micro: 0.1313
F1-macro: 0.1119
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: 1.5e-06
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 30
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
F1-micro
F1-macro
23.3966
1.0
78
7.9969
0.1313
0.1119
23.1247
2.0
156
7.9954
0.1313
0.1119
23.3807
3.0
234
7.9941
0.1313
0.1119
23.0229
4.0
312
7.9938
0.1313
0.1119
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1
