---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- rexarski/TCFD_disclosure
base_model: distilroberta-base
model-index:
- name: distilroberta-tcfd-disclosure
  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. -->

# distilroberta-tcfd-disclosure

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8681

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 5    | 2.3837          |
| 2.3918        | 2.0   | 10   | 2.3787          |
| 2.3918        | 3.0   | 15   | 2.3704          |
| 2.3754        | 4.0   | 20   | 2.3623          |
| 2.3754        | 5.0   | 25   | 2.3396          |
| 2.2976        | 6.0   | 30   | 2.2599          |
| 2.2976        | 7.0   | 35   | 2.1095          |
| 2.0439        | 8.0   | 40   | 2.0184          |
| 2.0439        | 9.0   | 45   | 1.9059          |
| 1.6799        | 10.0  | 50   | 1.8469          |
| 1.6799        | 11.0  | 55   | 1.8089          |
| 1.2948        | 12.0  | 60   | 1.7263          |
| 1.2948        | 13.0  | 65   | 1.7250          |
| 0.9621        | 14.0  | 70   | 1.8106          |
| 0.9621        | 15.0  | 75   | 1.8073          |
| 0.7356        | 16.0  | 80   | 1.8681          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3