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vmw-xlm-focal-lr-3e-5 – AI Model by jaycentg | AlphaNeural AI
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vmw-xlm-focal-lr-3e-5
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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-lr-3e-5
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: 7.9885
F1-micro: 0.1783
F1-macro: 0.1212
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: 3e-05
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
23.4304
1.0
78
7.9835
0.1312
0.1120
23.1213
2.0
156
7.9505
0.1327
0.1032
23.3218
3.0
234
7.9915
0.1841
0.1235
23.0612
4.0
312
7.9885
0.1783
0.1212
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1
