File size: 2,624 Bytes
54d1ca2 |
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 |
---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: cnn-dailymail_model
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. -->
# cnn-dailymail_model
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0614
- Rouge: {'rouge1': 0.244712987386149, 'rouge2': 0.09089741156156833, 'rougeL': 0.20130780704255938, 'rougeLsum': 0.2014458092407283}
- Bleu: 0.1054
- Perplexity: 7.8927
- 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge | Bleu | Perplexity | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------------------------:|:------:|:----------:|:-------:|
| No log | 1.0 | 75 | 2.1554 | {'rouge1': 0.24004289659476444, 'rouge2': 0.08899351952220792, 'rougeL': 0.19620544968984488, 'rougeLsum': 0.19620948547030603} | 0.1014 | None | 19.0 |
| No log | 2.0 | 150 | 2.0823 | {'rouge1': 0.2395197299581741, 'rouge2': 0.08874595402755553, 'rougeL': 0.19692733055468523, 'rougeLsum': 0.19727630390573275} | 0.1010 | 8.6314 | 19.0 |
| No log | 3.0 | 225 | 2.0659 | {'rouge1': 0.24346041598310222, 'rouge2': 0.09042566103154628, 'rougeL': 0.20046289165406544, 'rougeLsum': 0.2007357619831489} | 0.1041 | 8.0232 | 19.0 |
| No log | 4.0 | 300 | 2.0614 | {'rouge1': 0.244712987386149, 'rouge2': 0.09089741156156833, 'rougeL': 0.20130780704255938, 'rougeLsum': 0.2014458092407283} | 0.1054 | 7.8927 | 19.0 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2
|