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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- sem_eval2010_task8
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-sem
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: sem_eval2010_task8
      type: sem_eval2010_task8
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8314317261685683
---

<!-- 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. -->

# distilbert-base-uncased-finetuned-sem

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the sem_eval2010_task8 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6704
- Accuracy: 0.8314

## 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-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9556        | 1.0   | 800  | 0.7859          | 0.7814   |
| 0.6136        | 2.0   | 1600 | 0.6069          | 0.8193   |
| 0.4314        | 3.0   | 2400 | 0.6179          | 0.8211   |
| 0.2315        | 4.0   | 3200 | 0.6617          | 0.8281   |
| 0.1655        | 5.0   | 4000 | 0.6704          | 0.8314   |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6
