SharonTudi/DIALOGUE_second_model

1---2license: apache-2.03base_model: bert-base-cased4tags:5- generated_from_trainer6metrics:7- precision8- recall9- f110- accuracy11model-index:12- name: DIALOGUE_second_model13  results: []14---15 16<!-- This model card has been generated automatically according to the information the Trainer had access to. You17should probably proofread and complete it, then remove this comment. -->18 19# DIALOGUE_second_model20 21This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.22It achieves the following results on the evaluation set:23- Loss: 0.336424- Precision: 0.976225- Recall: 0.973726- F1: 0.973627- Accuracy: 0.973728 29## Model description30 31More information needed32 33## Intended uses & limitations34 35More information needed36 37## Training and evaluation data38 39More information needed40 41## Training procedure42 43### Training hyperparameters44 45The following hyperparameters were used during training:46- learning_rate: 1e-0547- train_batch_size: 848- eval_batch_size: 849- seed: 4250- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0851- lr_scheduler_type: linear52- num_epochs: 353 54### Training results55 56| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |57|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|58| 1.3667        | 0.31  | 15   | 1.2505          | 0.2468    | 0.4868 | 0.3263 | 0.4868   |59| 1.1649        | 0.62  | 30   | 1.0587          | 0.8659    | 0.7105 | 0.6935 | 0.7105   |60| 1.0288        | 0.94  | 45   | 0.8905          | 0.9479    | 0.9342 | 0.9331 | 0.9342   |61| 0.8541        | 1.25  | 60   | 0.7069          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |62| 0.6833        | 1.56  | 75   | 0.5616          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |63| 0.6072        | 1.88  | 90   | 0.4586          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |64| 0.4665        | 2.19  | 105  | 0.3944          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |65| 0.4274        | 2.5   | 120  | 0.3563          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |66| 0.4116        | 2.81  | 135  | 0.3364          | 0.9762    | 0.9737 | 0.9736 | 0.9737   |67 68 69### Framework versions70 71- Transformers 4.37.072- Pytorch 2.1.0+cu12173- Datasets 2.16.174- Tokenizers 0.15.075