End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-large-uncased
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: trainer
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: cola
+      split: validation
+      args: cola
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8465963566634708
+    - name: F1
+      type: f1
+      value: 0.8064540073113251
+    - name: Precision
+      type: precision
+      value: 0.840606542828289
+    - name: Recall
+      type: recall
+      value: 0.7876439727431708
+---
+
+<!-- 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. -->
+
+# trainer
+
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4490
+- Accuracy: 0.8466
+- F1: 0.8065
+- Precision: 0.8406
+- Recall: 0.7876
+
+## 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: 8
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- 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 | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| No log        | 1.0   | 267  | 0.3860          | 0.8370   | 0.7999 | 0.8184    | 0.7876 |
+| 0.3455        | 2.0   | 534  | 0.4490          | 0.8466   | 0.8065 | 0.8406    | 0.7876 |
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.1

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,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "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": "4.37.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+size 1340622760

runs/Feb10_14-10-25_4c5fee1ac69e/events.out.tfevents.1707574236.4c5fee1ac69e.34.0

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training_args.bin

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