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---
library_name: transformers
base_model: google/muril-large-cased
tags:
- generated_from_trainer
model-index:
- name: muril-large-cased-tweet-devnagri-grouped
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-large-cased-tweet-devnagri-grouped
This model is a fine-tuned version of [google/muril-large-cased](https://huggingface.co/google/muril-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4110
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:------:|:---------------:|
| No log | 0.0478 | 5000 | 2.5496 |
| No log | 0.0955 | 10000 | 2.1840 |
| No log | 0.1433 | 15000 | 2.0172 |
| No log | 0.1910 | 20000 | 1.9188 |
| No log | 0.2388 | 25000 | 1.8525 |
| No log | 0.2865 | 30000 | 1.8047 |
| No log | 0.3343 | 35000 | 1.7694 |
| No log | 0.3820 | 40000 | 1.7406 |
| No log | 0.4298 | 45000 | 1.7076 |
| No log | 0.4775 | 50000 | 1.6848 |
| No log | 0.5253 | 55000 | 1.6713 |
| No log | 0.5730 | 60000 | 1.6543 |
| No log | 0.6208 | 65000 | 1.6364 |
| No log | 0.6685 | 70000 | 1.6226 |
| No log | 0.7163 | 75000 | 1.6103 |
| No log | 0.7640 | 80000 | 1.5976 |
| No log | 0.8118 | 85000 | 1.5925 |
| No log | 0.8595 | 90000 | 1.5883 |
| No log | 0.9073 | 95000 | 1.5763 |
| No log | 0.9550 | 100000 | 1.5581 |
| 1.9195 | 1.0028 | 105000 | 1.5774 |
| 1.9195 | 1.0505 | 110000 | 1.5507 |
| 1.9195 | 1.0983 | 115000 | 1.5728 |
| 1.9195 | 1.1460 | 120000 | 1.5328 |
| 1.9195 | 1.1938 | 125000 | 1.5265 |
| 1.9195 | 1.2415 | 130000 | 1.5199 |
| 1.9195 | 1.2893 | 135000 | 1.5216 |
| 1.9195 | 1.3370 | 140000 | 1.5098 |
| 1.9195 | 1.3848 | 145000 | 1.5061 |
| 1.9195 | 1.4325 | 150000 | 1.4985 |
| 1.9195 | 1.4803 | 155000 | 1.4943 |
| 1.9195 | 1.5280 | 160000 | 1.4933 |
| 1.9195 | 1.5758 | 165000 | 1.4853 |
| 1.9195 | 1.6235 | 170000 | 1.4778 |
| 1.9195 | 1.6713 | 175000 | 1.4797 |
| 1.9195 | 1.7190 | 180000 | 1.4702 |
| 1.9195 | 1.7668 | 185000 | 1.4958 |
| 1.9195 | 1.8145 | 190000 | 1.4683 |
| 1.9195 | 1.8623 | 195000 | 1.4748 |
| 1.9195 | 1.9100 | 200000 | 1.4560 |
| 1.9195 | 1.9578 | 205000 | 1.4553 |
| 1.5744 | 2.0055 | 210000 | 1.4431 |
| 1.5744 | 2.0533 | 215000 | 1.4432 |
| 1.5744 | 2.1010 | 220000 | 1.4446 |
| 1.5744 | 2.1488 | 225000 | 1.4407 |
| 1.5744 | 2.1965 | 230000 | 1.4454 |
| 1.5744 | 2.2443 | 235000 | 1.4371 |
| 1.5744 | 2.2920 | 240000 | 1.4351 |
| 1.5744 | 2.3398 | 245000 | 1.4291 |
| 1.5744 | 2.3875 | 250000 | 1.4293 |
| 1.5744 | 2.4353 | 255000 | 1.4245 |
| 1.5744 | 2.4830 | 260000 | 1.4253 |
| 1.5744 | 2.5308 | 265000 | 1.4305 |
| 1.5744 | 2.5785 | 270000 | 1.4221 |
| 1.5744 | 2.6263 | 275000 | 1.4181 |
| 1.5744 | 2.6740 | 280000 | 1.4146 |
| 1.5744 | 2.7218 | 285000 | 1.4149 |
| 1.5744 | 2.7695 | 290000 | 1.4131 |
| 1.5744 | 2.8173 | 295000 | 1.4155 |
| 1.5744 | 2.8650 | 300000 | 1.4137 |
| 1.5744 | 2.9128 | 305000 | 1.4119 |
| 1.5744 | 2.9605 | 310000 | 1.4070 |
### Framework versions
- Transformers 4.45.0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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