dipteshkanojia
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update model card README.md
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README.md
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@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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## Model description
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- seed: 43
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.2577 | 25.79 | 3224 | 1.1441 | 0.7082 | 0.6455 | 0.6302 | 0.6337 |
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| 0.2336 | 27.78 | 3472 | 1.1693 | 0.6982 | 0.6405 | 0.6242 | 0.6254 |
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| 0.2155 | 29.76 | 3720 | 1.1397 | 0.7042 | 0.6456 | 0.6405 | 0.6396 |
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| 0.2086 | 31.74 | 3968 | 1.1803 | 0.7002 | 0.6408 | 0.6302 | 0.6278 |
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| 0.1923 | 33.73 | 4216 | 1.2296 | 0.7002 | 0.6399 | 0.6265 | 0.6273 |
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### Framework versions
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This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9319
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- Accuracy: 0.6982
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- Precision: 0.6327
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- Recall: 0.6314
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- F1: 0.6320
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## Model description
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- seed: 43
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 25
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 1.0542 | 1.98 | 248 | 0.9786 | 0.5976 | 0.3936 | 0.5454 | 0.4330 |
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| 0.9307 | 3.97 | 496 | 0.8836 | 0.5996 | 0.4072 | 0.5604 | 0.4399 |
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| 0.8323 | 5.95 | 744 | 0.8266 | 0.5996 | 0.5508 | 0.5720 | 0.4527 |
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| 0.7554 | 7.94 | 992 | 0.8006 | 0.6318 | 0.5601 | 0.5838 | 0.5232 |
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| 0.6821 | 9.92 | 1240 | 0.8777 | 0.6740 | 0.5929 | 0.5875 | 0.5836 |
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| 0.6173 | 11.9 | 1488 | 0.8389 | 0.6640 | 0.5918 | 0.6031 | 0.5881 |
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| 0.5552 | 13.89 | 1736 | 0.9003 | 0.6962 | 0.6240 | 0.6160 | 0.6191 |
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| 0.4932 | 15.87 | 1984 | 0.8979 | 0.6982 | 0.6266 | 0.6231 | 0.6245 |
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| 0.4446 | 17.86 | 2232 | 0.9104 | 0.7002 | 0.6310 | 0.6290 | 0.6298 |
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| 0.4084 | 19.84 | 2480 | 0.9284 | 0.7002 | 0.6278 | 0.6255 | 0.6264 |
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| 0.3763 | 21.82 | 2728 | 0.9228 | 0.7082 | 0.6436 | 0.6380 | 0.6398 |
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| 0.3575 | 23.81 | 2976 | 0.9319 | 0.6982 | 0.6327 | 0.6314 | 0.6320 |
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### Framework versions
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