File size: 2,231 Bytes
8804de6 |
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 |
---
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: Muril-base-finetune-Telugu-qc
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-finetune-Telugu-qc
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: 1.6250
- Precision: 0.7716
- Recall: 0.7647
- Accuracy: 0.7647
- F1-score: 0.7587
## 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-05
- 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 1.7858 | 1.0 | 32 | 1.7821 | 0.0454 | 0.2130 | 0.2130 | 0.0748 |
| 1.7526 | 2.0 | 64 | 1.7539 | 0.1754 | 0.2860 | 0.2860 | 0.1866 |
| 1.7112 | 3.0 | 96 | 1.7232 | 0.3352 | 0.3043 | 0.3043 | 0.2168 |
| 1.6655 | 4.0 | 128 | 1.6832 | 0.7122 | 0.6166 | 0.6166 | 0.6194 |
| 1.6217 | 5.0 | 160 | 1.6496 | 0.7708 | 0.7688 | 0.7688 | 0.7629 |
| 1.5898 | 6.0 | 192 | 1.6431 | 0.7618 | 0.7424 | 0.7424 | 0.7379 |
| 1.5678 | 7.0 | 224 | 1.6285 | 0.7697 | 0.7627 | 0.7627 | 0.7565 |
| 1.5572 | 8.0 | 256 | 1.6250 | 0.7716 | 0.7647 | 0.7647 | 0.7587 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|