---
base_model: haryoaw/scenario-MDBT-TCR_data-en-massive_all_1_1
datasets:
- massive
library_name: transformers
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: scenario-NON-KD-PO-COPY-D2_data-en-massive_all_1_155
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# scenario-NON-KD-PO-COPY-D2_data-en-massive_all_1_155

This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-massive_all_1_1](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-massive_all_1_1) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 6.1447
- Accuracy: 0.4126
- F1: 0.3790

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 55
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:|
| 0.0188        | 13.8889 | 5000  | 4.9762          | 0.4187   | 0.3726 |
| 0.0015        | 27.7778 | 10000 | 6.1447          | 0.4126   | 0.3790 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.19.1