ShaunThayil/training2-bert-uncased-18-09-23 18:09

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: training-1
+  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. -->
+
+# training-1
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0188
+- Accuracy: 0.9957
+- Precision: 0.9979
+- Recall: 0.9936
+- F1: 0.9957
+
+## 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: 1e-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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 0.99  | 175  | 0.0323          | 0.9925   | 1.0       | 0.9850 | 0.9925 |
+| 0.1307        | 1.99  | 350  | 0.0291          | 0.9936   | 1.0       | 0.9872 | 0.9935 |
+| 0.0299        | 2.98  | 525  | 0.0201          | 0.9957   | 0.9979    | 0.9936 | 0.9957 |
+| 0.024         | 3.98  | 700  | 0.0188          | 0.9957   | 0.9979    | 0.9936 | 0.9957 |
+| 0.0183        | 4.97  | 875  | 0.0188          | 0.9957   | 0.9979    | 0.9936 | 0.9957 |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.2.0.dev20230913+cu121
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "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": "4.33.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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training_args.bin

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