avkumararun/bert-tiny

README.md

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+---
+library_name: transformers
+license: mit
+base_model: prajjwal1/bert-tiny
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: results
+  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. -->
+
+# results
+
+This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0985
+- Accuracy: 0.91
+- F1: 0.9096
+- Precision: 0.9139
+- Recall: 0.9123
+
+## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 125  | 1.5109          | 0.59     | 0.6026 | 0.7073    | 0.5895 |
+| No log        | 2.0   | 250  | 1.3482          | 0.828    | 0.8293 | 0.8313    | 0.8301 |
+| No log        | 3.0   | 375  | 1.2057          | 0.882    | 0.8806 | 0.8837    | 0.8850 |
+| 1.4080        | 4.0   | 500  | 1.1231          | 0.906    | 0.9056 | 0.9099    | 0.9085 |
+| 1.4080        | 5.0   | 625  | 1.0985          | 0.91     | 0.9096 | 0.9139    | 0.9123 |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.9.0+cpu
+- Datasets 4.0.0
+- Tokenizers 0.22.2

config.json

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+{
+  "add_cross_attention": false,
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": null,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 128,
+  "id2label": {
+    "0": "QUESTION",
+    "1": "STATEMENT",
+    "2": "REQUIREMENT",
+    "3": "GREETING",
+    "4": "FEEDBACK"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 512,
+  "is_decoder": false,
+  "label2id": {
+    "FEEDBACK": 4,
+    "GREETING": 3,
+    "QUESTION": 0,
+    "REQUIREMENT": 2,
+    "STATEMENT": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 2,
+  "num_hidden_layers": 2,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "type_vocab_size": 2,
+  "use_cache": false,
+  "vocab_size": 30522
+}

model.safetensors

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+size 17550852

tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "cls_token": "[CLS]",
+  "do_lower_case": false,
+  "is_local": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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