|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: muril-base-cased-finetuned-code-mixed-DS |
|
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. --> |
|
|
|
# muril-base-cased-finetuned-code-mixed-DS |
|
|
|
This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co./google/muril-base-cased) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9319 |
|
- Accuracy: 0.6982 |
|
- Precision: 0.6327 |
|
- Recall: 0.6314 |
|
- F1: 0.6320 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 43 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 1.0542 | 1.98 | 248 | 0.9786 | 0.5976 | 0.3936 | 0.5454 | 0.4330 | |
|
| 0.9307 | 3.97 | 496 | 0.8836 | 0.5996 | 0.4072 | 0.5604 | 0.4399 | |
|
| 0.8323 | 5.95 | 744 | 0.8266 | 0.5996 | 0.5508 | 0.5720 | 0.4527 | |
|
| 0.7554 | 7.94 | 992 | 0.8006 | 0.6318 | 0.5601 | 0.5838 | 0.5232 | |
|
| 0.6821 | 9.92 | 1240 | 0.8777 | 0.6740 | 0.5929 | 0.5875 | 0.5836 | |
|
| 0.6173 | 11.9 | 1488 | 0.8389 | 0.6640 | 0.5918 | 0.6031 | 0.5881 | |
|
| 0.5552 | 13.89 | 1736 | 0.9003 | 0.6962 | 0.6240 | 0.6160 | 0.6191 | |
|
| 0.4932 | 15.87 | 1984 | 0.8979 | 0.6982 | 0.6266 | 0.6231 | 0.6245 | |
|
| 0.4446 | 17.86 | 2232 | 0.9104 | 0.7002 | 0.6310 | 0.6290 | 0.6298 | |
|
| 0.4084 | 19.84 | 2480 | 0.9284 | 0.7002 | 0.6278 | 0.6255 | 0.6264 | |
|
| 0.3763 | 21.82 | 2728 | 0.9228 | 0.7082 | 0.6436 | 0.6380 | 0.6398 | |
|
| 0.3575 | 23.81 | 2976 | 0.9319 | 0.6982 | 0.6327 | 0.6314 | 0.6320 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.20.1 |
|
- Pytorch 1.10.1+cu111 |
|
- Datasets 2.3.2 |
|
- Tokenizers 0.12.1 |
|
|
