transformers pytorch tensorboard distilbert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert_sa_GLUE_Experiment_rte_192
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE RTE
      type: glue
      config: rte
      split: validation
      args: rte
    metrics:
    - type: accuracy
      value: 0.5270758122743683
      name: Accuracy
---

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# distilbert_sa_GLUE_Experiment_rte_192

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6920
- Accuracy: 0.5271

## 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: 256
- eval_batch_size: 256
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6951        | 1.0   | 10   | 0.6927          | 0.5271   |
| 0.6935        | 2.0   | 20   | 0.6925          | 0.5271   |
| 0.692         | 3.0   | 30   | 0.6931          | 0.5162   |
| 0.694         | 4.0   | 40   | 0.6932          | 0.5090   |
| 0.6923        | 5.0   | 50   | 0.6950          | 0.4729   |
| 0.6932        | 6.0   | 60   | 0.6921          | 0.5271   |
| 0.6926        | 7.0   | 70   | 0.6928          | 0.5235   |
| 0.6917        | 8.0   | 80   | 0.6929          | 0.5271   |
| 0.6896        | 9.0   | 90   | 0.6920          | 0.5271   |
| 0.6758        | 10.0  | 100  | 0.7009          | 0.4801   |
| 0.6273        | 11.0  | 110  | 0.7272          | 0.4946   |
| 0.5267        | 12.0  | 120  | 0.7684          | 0.5199   |
| 0.4413        | 13.0  | 130  | 0.8273          | 0.4946   |
| 0.3725        | 14.0  | 140  | 0.8790          | 0.4946   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
