---
license: apache-2.0
base_model: kennethge123/superglue_rte-bert-base-uncased
tags:
- generated_from_trainer
datasets:
- bigbench
metrics:
- accuracy
model-index:
- name: entailed_after_rte-bert-base-uncased
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: bigbench
      type: bigbench
      config: entailed_polarity
      split: validation
      args: entailed_polarity
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5714285714285714
---

<!-- 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. -->

# entailed_after_rte-bert-base-uncased

This model is a fine-tuned version of [kennethge123/superglue_rte-bert-base-uncased](https://huggingface.co/kennethge123/superglue_rte-bert-base-uncased) on the bigbench dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7322
- Accuracy: 0.5714

## 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: 4
- eval_batch_size: 32
- 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   | 30   | 0.6876          | 0.5714   |
| No log        | 2.0   | 60   | 0.8029          | 0.5714   |
| No log        | 3.0   | 90   | 0.7246          | 0.5714   |
| No log        | 4.0   | 120  | 0.7152          | 0.5714   |
| No log        | 5.0   | 150  | 0.7887          | 0.5714   |
| No log        | 6.0   | 180  | 0.7498          | 0.5714   |
| No log        | 7.0   | 210  | 0.8149          | 0.4286   |
| No log        | 8.0   | 240  | 0.7055          | 0.5714   |
| No log        | 9.0   | 270  | 0.7209          | 0.5714   |
| No log        | 10.0  | 300  | 0.6922          | 0.5714   |
| No log        | 11.0  | 330  | 0.7186          | 0.5714   |
| No log        | 12.0  | 360  | 0.6916          | 0.5714   |
| No log        | 13.0  | 390  | 0.7233          | 0.5714   |
| No log        | 14.0  | 420  | 0.7109          | 0.5714   |
| No log        | 15.0  | 450  | 0.7051          | 0.5714   |
| No log        | 16.0  | 480  | 0.6968          | 0.5714   |
| 0.7046        | 17.0  | 510  | 0.7068          | 0.5714   |
| 0.7046        | 18.0  | 540  | 0.7319          | 0.5714   |
| 0.7046        | 19.0  | 570  | 0.7301          | 0.5714   |
| 0.7046        | 20.0  | 600  | 0.7322          | 0.5714   |


### Framework versions

- Transformers 4.37.0
- Pytorch 1.13.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.2