File size: 3,062 Bytes
3a5a162 |
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 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 |
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- matthews_correlation
model-index:
- name: paraphrase-MiniLM-L12-v2-CoLA
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: cola
split: validation
args: cola
metrics:
- name: Matthews Correlation
type: matthews_correlation
value: 0.49464326454019025
---
<!-- 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. -->
# paraphrase-MiniLM-L12-v2-CoLA
This model is a fine-tuned version of [sentence-transformers/paraphrase-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L12-v2) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9375
- Matthews Correlation: 0.4946
## 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: 8e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 30198
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 16.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| 0.5747 | 1.0 | 67 | 0.5394 | 0.3455 |
| 0.5025 | 2.0 | 134 | 0.4999 | 0.4270 |
| 0.3698 | 3.0 | 201 | 0.4636 | 0.5057 |
| 0.2969 | 4.0 | 268 | 0.5309 | 0.4751 |
| 0.2275 | 5.0 | 335 | 0.6238 | 0.4775 |
| 0.1859 | 6.0 | 402 | 0.6315 | 0.4867 |
| 0.1517 | 7.0 | 469 | 0.7783 | 0.4695 |
| 0.1016 | 8.0 | 536 | 0.6762 | 0.4901 |
| 0.1017 | 9.0 | 603 | 0.7412 | 0.5046 |
| 0.0898 | 10.0 | 670 | 0.7719 | 0.4877 |
| 0.0527 | 11.0 | 737 | 0.8627 | 0.4955 |
| 0.0582 | 12.0 | 804 | 0.8986 | 0.4738 |
| 0.074 | 13.0 | 871 | 0.9469 | 0.4942 |
| 0.0508 | 14.0 | 938 | 0.9436 | 0.4918 |
| 0.024 | 15.0 | 1005 | 0.9391 | 0.4919 |
| 0.0458 | 16.0 | 1072 | 0.9375 | 0.4946 |
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.1
|