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---
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
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