---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-finetuned-sst-2-english_07112024T180048
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-sst-2-english_07112024T180048

This model is a fine-tuned version of [distilbert/distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4594
- F1: 0.8486
- Learning Rate: 0.0

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 600
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | F1     | Rate   |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| No log        | 0.9942  | 86   | 1.7769          | 0.0796 | 0.0000 |
| No log        | 2.0     | 173  | 1.7161          | 0.2057 | 0.0000 |
| No log        | 2.9942  | 259  | 1.6015          | 0.3386 | 0.0000 |
| No log        | 4.0     | 346  | 1.4321          | 0.4359 | 0.0000 |
| No log        | 4.9942  | 432  | 1.2548          | 0.5262 | 0.0000 |
| 1.5627        | 6.0     | 519  | 1.0659          | 0.5697 | 0.0000 |
| 1.5627        | 6.9942  | 605  | 0.9261          | 0.6140 | 1e-05  |
| 1.5627        | 8.0     | 692  | 0.8197          | 0.6649 | 0.0000 |
| 1.5627        | 8.9942  | 778  | 0.7274          | 0.7060 | 0.0000 |
| 1.5627        | 10.0    | 865  | 0.6496          | 0.7548 | 0.0000 |
| 1.5627        | 10.9942 | 951  | 0.5997          | 0.7741 | 0.0000 |
| 0.7439        | 12.0    | 1038 | 0.5462          | 0.8076 | 0.0000 |
| 0.7439        | 12.9942 | 1124 | 0.5300          | 0.8141 | 0.0000 |
| 0.7439        | 14.0    | 1211 | 0.4898          | 0.8314 | 0.0000 |
| 0.7439        | 14.9942 | 1297 | 0.4791          | 0.8382 | 0.0000 |
| 0.7439        | 16.0    | 1384 | 0.4756          | 0.8399 | 0.0000 |
| 0.7439        | 16.9942 | 1470 | 0.4668          | 0.8457 | 0.0000 |
| 0.3573        | 18.0    | 1557 | 0.4600          | 0.8489 | 5e-07  |
| 0.3573        | 18.9942 | 1643 | 0.4594          | 0.8486 | 1e-07  |
| 0.3573        | 19.8844 | 1720 | 0.4596          | 0.8483 | 0.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.19.1