transformers tensorboard safetensors distilbert text-classification generated_from_trainer dataset:generator base_model:distilbert/distilbert-base-uncased base_model:finetune:distilbert/distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: distilbert/distilbert-base-uncased
datasets:
- generator
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distil_low_lr
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: generator
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - type: accuracy
      value: 0.745
      name: Accuracy
---

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# distil_low_lr

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8611
- Accuracy: 0.745

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 25   | 0.6622          | 0.5975   |
| No log        | 2.0   | 50   | 0.6039          | 0.67     |
| No log        | 3.0   | 75   | 0.5630          | 0.71     |
| No log        | 4.0   | 100  | 0.5624          | 0.7075   |
| No log        | 5.0   | 125  | 0.5749          | 0.7325   |
| No log        | 6.0   | 150  | 0.5818          | 0.73     |
| No log        | 7.0   | 175  | 0.6017          | 0.735    |
| No log        | 8.0   | 200  | 0.6407          | 0.735    |
| No log        | 9.0   | 225  | 0.6702          | 0.74     |
| No log        | 10.0  | 250  | 0.6999          | 0.74     |
| No log        | 11.0  | 275  | 0.7251          | 0.7325   |
| No log        | 12.0  | 300  | 0.7472          | 0.735    |
| No log        | 13.0  | 325  | 0.7647          | 0.745    |
| No log        | 14.0  | 350  | 0.7962          | 0.74     |
| No log        | 15.0  | 375  | 0.8120          | 0.7325   |
| No log        | 16.0  | 400  | 0.8283          | 0.745    |
| No log        | 17.0  | 425  | 0.8366          | 0.7425   |
| No log        | 18.0  | 450  | 0.8481          | 0.745    |
| No log        | 19.0  | 475  | 0.8588          | 0.7425   |
| 0.2302        | 20.0  | 500  | 0.8611          | 0.745    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
