End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-large-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: baseline_nli_bert-large
+  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. -->
+
+# baseline_nli_bert-large
+
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9293
+- Accuracy: 0.6163
+- Precision: 0.6163
+- Recall: 0.6163
+- F1 Score: 0.6185
+
+## 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: 3e-06
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 101
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1 Score |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| 1.0447        | 1.0   | 2583  | 0.9867          | 0.4602   | 0.4602    | 0.4602 | 0.4166   |
+| 0.9632        | 2.0   | 5166  | 0.9132          | 0.5926   | 0.5926    | 0.5926 | 0.5965   |
+| 0.9063        | 3.0   | 7749  | 0.8976          | 0.6076   | 0.6076    | 0.6076 | 0.6116   |
+| 0.846         | 4.0   | 10332 | 0.8826          | 0.6218   | 0.6218    | 0.6218 | 0.6212   |
+| 0.7975        | 5.0   | 12915 | 0.9189          | 0.6136   | 0.6136    | 0.6136 | 0.6169   |
+| 0.7605        | 6.0   | 15498 | 0.9293          | 0.6163   | 0.6163    | 0.6163 | 0.6185   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "bert-large-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": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

pytorch_model.bin

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training_args.bin

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