---
base_model: neal49/distilbert-sst2-runglue
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dnd
  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. -->

# dnd

This model is a fine-tuned version of [neal49/distilbert-sst2-runglue](https://huggingface.co/neal49/distilbert-sst2-runglue) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4907
- Accuracy: 0.8246

## 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: 2e-06
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 15   | 0.6813          | 0.5789   |
| No log        | 2.0   | 30   | 0.6725          | 0.5789   |
| No log        | 3.0   | 45   | 0.6588          | 0.6140   |
| No log        | 4.0   | 60   | 0.6536          | 0.6140   |
| No log        | 5.0   | 75   | 0.6524          | 0.6140   |
| No log        | 6.0   | 90   | 0.6426          | 0.6140   |
| No log        | 7.0   | 105  | 0.6333          | 0.6316   |
| No log        | 8.0   | 120  | 0.6148          | 0.6491   |
| No log        | 9.0   | 135  | 0.6081          | 0.6491   |
| No log        | 10.0  | 150  | 0.5724          | 0.7018   |
| No log        | 11.0  | 165  | 0.5984          | 0.6842   |
| No log        | 12.0  | 180  | 0.5328          | 0.7368   |
| No log        | 13.0  | 195  | 0.5419          | 0.7719   |
| No log        | 14.0  | 210  | 0.5271          | 0.7719   |
| No log        | 15.0  | 225  | 0.5188          | 0.7719   |
| No log        | 16.0  | 240  | 0.5283          | 0.7719   |
| No log        | 17.0  | 255  | 0.5012          | 0.7719   |
| No log        | 18.0  | 270  | 0.4863          | 0.7895   |
| No log        | 19.0  | 285  | 0.5329          | 0.7895   |
| No log        | 20.0  | 300  | 0.4861          | 0.8070   |
| No log        | 21.0  | 315  | 0.5065          | 0.8246   |
| No log        | 22.0  | 330  | 0.4864          | 0.8070   |
| No log        | 23.0  | 345  | 0.5060          | 0.8246   |
| No log        | 24.0  | 360  | 0.4752          | 0.8246   |
| No log        | 25.0  | 375  | 0.4983          | 0.8246   |
| No log        | 26.0  | 390  | 0.4925          | 0.8246   |
| No log        | 27.0  | 405  | 0.4774          | 0.8246   |
| No log        | 28.0  | 420  | 0.4804          | 0.8246   |
| No log        | 29.0  | 435  | 0.4927          | 0.8246   |
| No log        | 30.0  | 450  | 0.4907          | 0.8246   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.2