File size: 2,022 Bytes
1546eee 4b08a2c 1546eee 4b08a2c 1546eee 4b08a2c 1546eee 4b08a2c 1546eee 4b08a2c 1546eee |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: distilbert-base-uncased-CoLA-finetuned-cola
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
args: cola
metrics:
- name: Matthews Correlation
type: matthews_correlation
value: 0.5689051637185746
---
<!-- 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. -->
# distilbert-base-uncased-CoLA-finetuned-cola
This model is a fine-tuned version of [textattack/distilbert-base-uncased-CoLA](https://huggingface.co/textattack/distilbert-base-uncased-CoLA) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6996
- Matthews Correlation: 0.5689
## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log | 1.0 | 134 | 0.6061 | 0.5074 |
| No log | 2.0 | 268 | 0.5808 | 0.5652 |
| No log | 3.0 | 402 | 0.6996 | 0.5689 |
| 0.0952 | 4.0 | 536 | 0.8249 | 0.5385 |
| 0.0952 | 5.0 | 670 | 0.8714 | 0.5567 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
|