transformers tensorboard safetensors gpt2 text-classification generated_from_trainer dataset:bigbench base_model:kennethge123/superglue_rte-gpt2 base_model:finetune:kennethge123/superglue_rte-gpt2 license:mit model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: kennethge123/superglue_rte-gpt2
datasets:
- bigbench
license: mit
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: entailed_after_rte-gpt2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: bigbench
      type: bigbench
      config: entailed_polarity
      split: validation
      args: entailed_polarity
    metrics:
    - type: accuracy
      value: 0.7142857142857143
      name: Accuracy
---

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# entailed_after_rte-gpt2

This model is a fine-tuned version of [kennethge123/superglue_rte-gpt2](https://huggingface.co/kennethge123/superglue_rte-gpt2) on the bigbench dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1865
- Accuracy: 0.7143

## 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   | 0.9025          | 0.3571   |
| No log        | 2.0   | 60   | 0.7155          | 0.5      |
| No log        | 3.0   | 90   | 1.0014          | 0.2857   |
| No log        | 4.0   | 120  | 0.9748          | 0.5714   |
| No log        | 5.0   | 150  | 0.9511          | 0.5714   |
| No log        | 6.0   | 180  | 1.0164          | 0.6429   |
| No log        | 7.0   | 210  | 1.6015          | 0.5      |
| No log        | 8.0   | 240  | 1.2833          | 0.6429   |
| No log        | 9.0   | 270  | 1.0093          | 0.7857   |
| No log        | 10.0  | 300  | 1.6339          | 0.6429   |
| No log        | 11.0  | 330  | 1.3461          | 0.5714   |
| No log        | 12.0  | 360  | 1.2949          | 0.6429   |
| No log        | 13.0  | 390  | 1.6343          | 0.6429   |
| No log        | 14.0  | 420  | 0.8418          | 0.8571   |
| No log        | 15.0  | 450  | 0.6750          | 0.8571   |
| No log        | 16.0  | 480  | 2.0221          | 0.6429   |
| 0.5929        | 17.0  | 510  | 0.7579          | 0.8571   |
| 0.5929        | 18.0  | 540  | 1.5713          | 0.7143   |
| 0.5929        | 19.0  | 570  | 1.0489          | 0.7143   |
| 0.5929        | 20.0  | 600  | 1.1865          | 0.7143   |


### Framework versions

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