SharonTudi/DIALOGUE_four_model

1---2license: apache-2.03base_model: distilbert-base-uncased4tags:5- generated_from_trainer6metrics:7- accuracy8- precision9- recall10- f111model-index:12- name: DIALOGUE_four_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_four_model20 21This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.22It achieves the following results on the evaluation set:23- Loss: 0.123724- Accuracy: 0.973725- Precision: 0.976226- Recall: 0.973727- F1: 0.973628 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: 3e-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 | Accuracy | Precision | Recall | F1     |57|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|58| 1.2597        | 0.31  | 15   | 1.0370          | 0.7105   | 0.6143    | 0.7105 | 0.6481 |59| 0.857         | 0.62  | 30   | 0.5686          | 0.9474   | 0.9565    | 0.9474 | 0.9468 |60| 0.5836        | 0.94  | 45   | 0.3401          | 0.9737   | 0.9762    | 0.9737 | 0.9736 |61| 0.317         | 1.25  | 60   | 0.2230          | 0.9737   | 0.9762    | 0.9737 | 0.9736 |62| 0.2482        | 1.56  | 75   | 0.1819          | 0.9737   | 0.9762    | 0.9737 | 0.9736 |63| 0.1655        | 1.88  | 90   | 0.1573          | 0.9737   | 0.9762    | 0.9737 | 0.9736 |64| 0.0814        | 2.19  | 105  | 0.1175          | 0.9737   | 0.9762    | 0.9737 | 0.9736 |65| 0.1098        | 2.5   | 120  | 0.1131          | 0.9737   | 0.9762    | 0.9737 | 0.9736 |66| 0.0862        | 2.81  | 135  | 0.1237          | 0.9737   | 0.9762    | 0.9737 | 0.9736 |67 68 69### Framework versions70 71- Transformers 4.36.272- Pytorch 2.1.0+cu12173- Datasets 2.16.174- Tokenizers 0.15.075