End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- precision
+- recall
+- accuracy
+model-index:
+- name: test_trainer
+  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. -->
+
+# test_trainer
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0633
+- F1: 0.3413
+- Precision: 0.2765
+- Recall: 0.4456
+- Accuracy: 0.7017
+
+## 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: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
+| 0.6981        | 1.0   | 285  | 0.6720          | 0.3035 | 0.2919    | 0.3161 | 0.7484   |
+| 0.6726        | 2.0   | 570  | 0.6554          | 0.3547 | 0.2740    | 0.5026 | 0.6828   |
+| 0.6402        | 3.0   | 855  | 0.6574          | 0.3609 | 0.2675    | 0.5544 | 0.6595   |
+| 0.568         | 4.0   | 1140 | 0.7293          | 0.3620 | 0.3154    | 0.4249 | 0.7403   |
+| 0.4926        | 5.0   | 1425 | 0.8515          | 0.3383 | 0.2883    | 0.4093 | 0.7224   |
+| 0.4303        | 6.0   | 1710 | 0.9507          | 0.3538 | 0.2813    | 0.4767 | 0.6981   |
+| 0.38          | 7.0   | 1995 | 1.0129          | 0.3366 | 0.2685    | 0.4508 | 0.6918   |
+| 0.3437        | 8.0   | 2280 | 1.0633          | 0.3413 | 0.2765    | 0.4456 | 0.7017   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "bert-base-cased",
+  "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": "4.38.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

model.safetensors

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+size 433270768

runs/Mar24_14-08-25_8a048ec7b58f/events.out.tfevents.1711289316.8a048ec7b58f.887.0

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training_args.bin

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