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Arunavaonly
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Bangla-twoclass-Sentiment-Analyzer

Text Classification
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PyTorch
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Safetensors
xlm-roberta
Generated from Trainer
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End of training

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  1. README.md +16 -15
  2. model.safetensors +1 -1
  3. runs/Feb24_13-59-05_e677ac1d2c6a/events.out.tfevents.1708783148.e677ac1d2c6a.5050.0 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1624
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- - F1: 0.9642
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  ## Model description
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@@ -44,25 +44,26 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - training_steps: 1800
 
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 0.34 | 200 | 0.3384 | 0.8842 |
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- | No log | 0.68 | 400 | 0.2352 | 0.9358 |
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- | 0.3357 | 1.02 | 600 | 0.1838 | 0.9458 |
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- | 0.3357 | 1.36 | 800 | 0.1768 | 0.9520 |
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- | 0.1794 | 1.69 | 1000 | 0.1650 | 0.9541 |
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- | 0.1794 | 2.03 | 1200 | 0.1629 | 0.9609 |
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- | 0.1794 | 2.37 | 1400 | 0.2278 | 0.9566 |
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- | 0.1305 | 2.71 | 1600 | 0.1633 | 0.9634 |
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- | 0.1305 | 3.05 | 1800 | 0.1624 | 0.9642 |
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  ### Framework versions
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- - Transformers 4.32.1
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.14.4
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- - Tokenizers 0.13.3
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.7755
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+ - F1: 0.6113
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - training_steps: 1800
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+ - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 2.53 | 200 | 0.9869 | 0.4635 |
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+ | No log | 5.06 | 400 | 0.8978 | 0.5858 |
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+ | 0.8692 | 7.59 | 600 | 1.1978 | 0.6149 |
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+ | 0.8692 | 10.13 | 800 | 1.5145 | 0.6112 |
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+ | 0.3138 | 12.66 | 1000 | 2.0353 | 0.6041 |
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+ | 0.3138 | 15.19 | 1200 | 2.4316 | 0.6203 |
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+ | 0.3138 | 17.72 | 1400 | 2.6025 | 0.6002 |
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+ | 0.0769 | 20.25 | 1600 | 2.6247 | 0.6082 |
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+ | 0.0769 | 22.78 | 1800 | 2.7755 | 0.6113 |
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  ### Framework versions
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+ - Transformers 4.37.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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