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---
license: mit
base_model: kennethge123/superglue_rte-gpt2
tags:
- generated_from_trainer
datasets:
- bigbench
metrics:
- accuracy
model-index:
- name: entailed_after_rte-gpt2
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: 0.7142857142857143
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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