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---
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
base_model: roberta-base
model-index:
- name: roberta-base-finetuned-cola
results: []
---
<!-- 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. -->
# roberta-base-finetuned-cola
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6074
- Matthews Correlation: 0.6221
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- total_eval_batch_size: 5
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- training precision: Mixed Precision
### Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.4536 | 1.0 | 534 | 0.4104 | 0.5738 |
| 0.4876 | 2.0 | 1068 | 0.5156 | 0.5729 |
| 0.1281 | 3.0 | 1602 | 0.5083 | 0.6145 |
| 0.0441 | 4.0 | 2136 | 0.5483 | 0.6119 |
| 0.2985 | 5.0 | 2670 | 0.6074 | 0.6221 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.10.0+cpu
- Datasets 2.7.1
- Tokenizers 0.12.0
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