File size: 2,144 Bytes
b1f8049 |
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 74 75 |
---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
model-index:
- name: bengali_news_article_summarization_mt5
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. -->
# bengali_news_article_summarization_mt5
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2111
## 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: 0.001
- train_batch_size: 20
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 160
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 0.99 | 83 | 0.8963 |
| No log | 2.0 | 167 | 0.3201 |
| 9.149 | 2.99 | 250 | 0.2583 |
| 9.149 | 3.99 | 334 | 0.2372 |
| 0.3009 | 5.0 | 418 | 0.2298 |
| 0.3009 | 5.99 | 501 | 0.2244 |
| 0.3009 | 7.0 | 585 | 0.2213 |
| 0.2524 | 8.0 | 669 | 0.2163 |
| 0.2524 | 8.99 | 752 | 0.2136 |
| 0.2306 | 10.0 | 836 | 0.2126 |
| 0.2306 | 10.99 | 919 | 0.2117 |
| 0.2176 | 11.99 | 1003 | 0.2120 |
| 0.2176 | 13.0 | 1087 | 0.2116 |
| 0.2176 | 13.99 | 1170 | 0.2111 |
| 0.2119 | 14.89 | 1245 | 0.2111 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
|