File size: 1,739 Bytes
608744e |
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 |
---
license: other
library_name: peft
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
base_model: facebook/opt-350m
model-index:
- name: opt-350m-pattern-based_finetuning_with_lora-mnli-mm-d2_fs1
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. -->
# opt-350m-pattern-based_finetuning_with_lora-mnli-mm-d2_fs1
This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6737
- Accuracy: 0.5308
## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3934 | 1.0 | 1 | 1.6780 | 0.5305 |
| 0.955 | 2.0 | 2 | 1.6763 | 0.5305 |
| 0.4831 | 3.0 | 3 | 1.6751 | 0.5305 |
| 0.8716 | 4.0 | 4 | 1.6742 | 0.5307 |
| 0.4978 | 5.0 | 5 | 1.6737 | 0.5308 |
### Framework versions
- PEFT 0.7.1.dev0
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0 |