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update model card README.md
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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: tabert-2k-indic_glue
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# tabert-2k-indic_glue
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This model is a fine-tuned version of [livinNector/tabert-2k](https://huggingface.co/livinNector/tabert-2k) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2663
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- Precision: 0.7940
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- Recall: 0.8281
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- F1: 0.8107
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- Accuracy: 0.9164
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 64
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- seed: 42
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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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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.5342 | 0.31 | 200 | 0.3755 | 0.6758 | 0.7277 | 0.7008 | 0.8753 |
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| 0.3625 | 0.62 | 400 | 0.3276 | 0.7279 | 0.7920 | 0.7586 | 0.8914 |
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| 0.3065 | 0.94 | 600 | 0.2855 | 0.7827 | 0.7980 | 0.7903 | 0.9050 |
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| 0.2321 | 1.25 | 800 | 0.2804 | 0.7860 | 0.8063 | 0.7960 | 0.9092 |
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| 0.1849 | 1.56 | 1000 | 0.2735 | 0.7946 | 0.8154 | 0.8049 | 0.9143 |
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| 0.1784 | 1.88 | 1200 | 0.2663 | 0.7940 | 0.8281 | 0.8107 | 0.9164 |
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### Framework versions
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- Transformers 4.29.2
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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