update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert-base-multilingual-cased-indic_glue
+  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. -->
+
+# distilbert-base-multilingual-cased-indic_glue
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2873
+- Precision: 0.8099
+- Recall: 0.8251
+- F1: 0.8175
+- Accuracy: 0.9114
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.6012        | 0.31  | 200  | 0.3849          | 0.7566    | 0.7108 | 0.7330 | 0.8722   |
+| 0.377         | 0.62  | 400  | 0.3365          | 0.7696    | 0.7837 | 0.7766 | 0.8886   |
+| 0.3205        | 0.94  | 600  | 0.3093          | 0.7875    | 0.7864 | 0.7869 | 0.8961   |
+| 0.2517        | 1.25  | 800  | 0.3050          | 0.8039    | 0.8131 | 0.8085 | 0.9050   |
+| 0.2034        | 1.56  | 1000 | 0.2950          | 0.8129    | 0.8130 | 0.8130 | 0.9098   |
+| 0.1968        | 1.88  | 1200 | 0.2873          | 0.8099    | 0.8251 | 0.8175 | 0.9114   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3