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finetuned-sentiment-withGPU – AI Model by sepidmnorozy | AlphaNeural AI
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sepidmnorozy
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finetuned-sentiment-withGPU
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transformers
pytorch
xlm-roberta
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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finetuning-sentiment-model-10-samples_withGPU
This model is a fine-tuned version of
xlm-roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3893
Accuracy: 0.8744
F1: 0.8684
Precision: 0.9126
Recall: 0.8283
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: 8
eval_batch_size: 8
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
Precision
Recall
0.3631
1.0
7088
0.3622
0.8638
0.8519
0.9334
0.7835
0.35
2.0
14176
0.3875
0.8714
0.8622
0.9289
0.8044
0.3262
3.0
21264
0.3893
0.8744
0.8684
0.9126
0.8283
Framework versions
Transformers 4.18.0
Pytorch 1.10.0
Datasets 2.0.0
Tokenizers 0.11.6
