End of training

README.md

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+---
+license: mit
+base_model: sagorsarker/bangla-bert-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: bangla-bert-base-MLTC-BB2
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bangla-bert-base-MLTC-BB2
+
+This model is a fine-tuned version of [sagorsarker/bangla-bert-base](https://huggingface.co/sagorsarker/bangla-bert-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4005
+- F1: 0.8514
+- F1 Weighted: 0.8504
+- Roc Auc: 0.8470
+- Accuracy: 0.5424
+- Hamming Loss: 0.1530
+- Jaccard Score: 0.7413
+- Zero One Loss: 0.4576
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | F1 Weighted | Roc Auc | Accuracy | Hamming Loss | Jaccard Score | Zero One Loss |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:-------:|:--------:|:------------:|:-------------:|:-------------:|
+| 0.4015        | 1.0   | 73   | 0.4027          | 0.8246 | 0.8201      | 0.8206  | 0.5039   | 0.1793       | 0.7016        | 0.4961        |
+| 0.3579        | 2.0   | 146  | 0.3583          | 0.8541 | 0.8548      | 0.8522  | 0.5553   | 0.1478       | 0.7453        | 0.4447        |
+| 0.2831        | 3.0   | 219  | 0.3768          | 0.8429 | 0.8402      | 0.8360  | 0.5398   | 0.1639       | 0.7284        | 0.4602        |
+| 0.1799        | 4.0   | 292  | 0.3565          | 0.8534 | 0.8534      | 0.8489  | 0.5604   | 0.1510       | 0.7443        | 0.4396        |
+| 0.1671        | 5.0   | 365  | 0.3724          | 0.8552 | 0.8547      | 0.8508  | 0.5681   | 0.1491       | 0.7470        | 0.4319        |
+| 0.1451        | 6.0   | 438  | 0.3773          | 0.8493 | 0.8484      | 0.8477  | 0.5450   | 0.1523       | 0.7381        | 0.4550        |
+| 0.0899        | 7.0   | 511  | 0.3986          | 0.8502 | 0.8494      | 0.8457  | 0.5398   | 0.1542       | 0.7394        | 0.4602        |
+| 0.0744        | 8.0   | 584  | 0.4005          | 0.8514 | 0.8504      | 0.8470  | 0.5424   | 0.1530       | 0.7413        | 0.4576        |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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