File size: 1,907 Bytes
daad4ab fb134ed daad4ab 8438d63 a756eb6 daad4ab a756eb6 daad4ab a756eb6 daad4ab fb134ed a756eb6 fb134ed daad4ab 4042536 daad4ab |
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 |
---
license: other
base_model: facebook/opt-125m
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: opt-125m-finetuned-mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: mnli
split: validation_matched
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.35517065715741214
---
<!-- 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-125m-finetuned-mnli
This model is a fine-tuned version of [facebook/opt-125m](https://huggingface.co/facebook/opt-125m) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7566
- Accuracy: 0.3552
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0726 | 1.0 | 1 | 1.7835 | 0.3536 |
| 0.1157 | 2.0 | 2 | 1.7566 | 0.3552 |
| 0.0624 | 3.0 | 3 | 1.7372 | 0.3548 |
| 0.07 | 4.0 | 4 | 1.7249 | 0.3544 |
| 0.0689 | 5.0 | 5 | 1.7189 | 0.3545 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|