File size: 2,253 Bytes
f6a3cc7 b174bad f6a3cc7 b174bad f6a3cc7 b174bad f6a3cc7 b174bad f6a3cc7 b174bad f6a3cc7 | 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 | ---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_rand_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny_bert_rand_20_v1_mnli
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MNLI
type: glue
args: mnli
metrics:
- name: Accuracy
type: accuracy
value: 0.5988608624898292
---
<!-- 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. -->
# tiny_bert_rand_20_v1_mnli
This model is a fine-tuned version of [Hartunka/tiny_bert_rand_20_v1](https://huggingface.co/Hartunka/tiny_bert_rand_20_v1) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8709
- Accuracy: 0.5989
## 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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9987 | 1.0 | 1534 | 0.9482 | 0.5350 |
| 0.9153 | 2.0 | 3068 | 0.8893 | 0.5831 |
| 0.8571 | 3.0 | 4602 | 0.8752 | 0.5966 |
| 0.8033 | 4.0 | 6136 | 0.8718 | 0.6011 |
| 0.7482 | 5.0 | 7670 | 0.8747 | 0.6078 |
| 0.6947 | 6.0 | 9204 | 0.9125 | 0.6129 |
| 0.6416 | 7.0 | 10738 | 0.9405 | 0.6155 |
| 0.5894 | 8.0 | 12272 | 1.0253 | 0.6039 |
| 0.5403 | 9.0 | 13806 | 1.1121 | 0.6019 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
|