File size: 2,246 Bytes
ccfbeb5 2d1cba7 ccfbeb5 |
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 |
---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-long-sumeczech
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. -->
# mt5-small-finetuned-long-sumeczech
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:
'eval_loss': 2.8214199542999268,
'eval_rouge1': 12.8674,
'eval_rouge2': 2.6891,
'eval_rougeL': 10.0662,
'eval_rougeLsum': 11.2368
## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:------:|:------:|:---------:|
| 3.5441 | 1.0 | 15064 | 3.0664 | 11.0135 | 1.7163 | 8.2892 | 9.7803 |
| 3.4047 | 2.0 | 30128 | 2.9725 | 10.5507 | 1.8535 | 8.0843 | 9.3876 |
| 3.2782 | 3.0 | 45192 | 2.9240 | 10.5563 | 1.9566 | 8.1144 | 9.4192 |
| 3.2035 | 4.0 | 60256 | 2.8895 | 10.5418 | 2.0105 | 8.132 | 9.3701 |
| 3.1538 | 5.0 | 75320 | 2.8712 | 10.6085 | 1.9954 | 8.1587 | 9.4499 |
| 3.1197 | 6.0 | 90384 | 2.8562 | 10.6394 | 2.0582 | 8.1855 | 9.4841 |
| 3.0976 | 7.0 | 105448 | 2.8439 | 10.7537 | 2.0754 | 8.2822 | 9.5754 |
| 3.0849 | 8.0 | 120512 | 2.8402 | 10.751 | 2.1081 | 8.2982 | 9.5911 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|