Abhi964

README.md

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+---
+library_name: transformers
+license: mit
+base_model: ai4bharat/IndicBERTv2-MLM-Back-TLM
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2
+  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. -->
+
+# Paraphrase_IndicBERTv2-MLM-Back-TLM_onfull_FT2
+
+This model is a fine-tuned version of [ai4bharat/IndicBERTv2-MLM-Back-TLM](https://huggingface.co/ai4bharat/IndicBERTv2-MLM-Back-TLM) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6694
+- Accuracy: 0.872
+- F1: 0.8716
+
+## 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: 2.448092452817481e-05
+- train_batch_size: 16
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.3163        | 1.0   | 313  | 0.3615          | 0.8485   | 0.8472 |
+| 0.2652        | 2.0   | 626  | 0.3545          | 0.867    | 0.8668 |
+| 0.1021        | 3.0   | 939  | 0.4961          | 0.864    | 0.8638 |
+| 0.0294        | 4.0   | 1252 | 0.6694          | 0.872    | 0.8716 |
+| 0.0941        | 5.0   | 1565 | 0.7800          | 0.8665   | 0.8664 |
+| 0.058         | 6.0   | 1878 | 0.8815          | 0.8645   | 0.8641 |
+| 0.0002        | 7.0   | 2191 | 0.8727          | 0.8655   | 0.8654 |
+| 0.004         | 8.0   | 2504 | 0.9035          | 0.8655   | 0.8653 |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "ai4bharat/IndicBERTv2-MLM-Back-TLM",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "embedding_size": 768,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 250000
+}

model.safetensors

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+size 1112195200

special_tokens_map.json

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+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
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+}

tokenizer_config.json

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+}

training_args.bin

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