File size: 2,057 Bytes
1b80be2 |
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: mHossain/ml_sum_v1
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ml_sum_v2
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. -->
# ml_sum_v2
This model is a fine-tuned version of [mHossain/ml_sum_v1](https://huggingface.co/mHossain/ml_sum_v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9401
- Rouge1: 8.1448
- Rouge2: 3.3615
- Rougel: 7.4641
- Rougelsum: 7.9361
- Gen Len: 19.0
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 312 | 2.1706 | 7.2919 | 2.8117 | 6.7418 | 7.1173 | 19.0 |
| 2.4911 | 2.0 | 625 | 2.1012 | 7.7986 | 3.0952 | 7.1505 | 7.5818 | 19.0 |
| 2.4911 | 3.0 | 937 | 2.0373 | 8.0535 | 3.2228 | 7.3877 | 7.8365 | 19.0 |
| 2.3572 | 4.0 | 1250 | 1.9865 | 8.1591 | 3.31 | 7.4577 | 7.9114 | 19.0 |
| 2.2455 | 4.99 | 1560 | 1.9401 | 8.1448 | 3.3615 | 7.4641 | 7.9361 | 19.0 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|