|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: t5-base-DreamBank-Generation-Char |
|
results: [] |
|
language: |
|
- en |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# t5-base-DreamBank-Generation-Char |
|
|
|
This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the DB emotion classification. |
|
It achieves the following results on the evaluation set (please note they refer to best uploaded model): |
|
- Loss: 0.3047 |
|
- Rouge1: 0.8609 |
|
- Rouge2: 0.7956 |
|
- Rougel: 0.8476 |
|
- Rougelsum: 0.8578 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
|
| No log | 1.0 | 24 | 0.4863 | 0.7670 | 0.6655 | 0.7575 | 0.7634 | |
|
| No log | 2.0 | 48 | 0.4284 | 0.6870 | 0.5207 | 0.6846 | 0.6875 | |
|
| No log | 3.0 | 72 | 0.3541 | 0.7659 | 0.6742 | 0.7600 | 0.7625 | |
|
| No log | 4.0 | 96 | 0.3211 | 0.8147 | 0.7251 | 0.7965 | 0.8078 | |
|
| No log | 5.0 | 120 | 0.3103 | 0.8400 | 0.7747 | 0.8313 | 0.8371 | |
|
| No log | 6.0 | 144 | 0.3220 | 0.8538 | 0.7867 | 0.8285 | 0.8515 | |
|
| No log | 7.0 | 168 | 0.3047 | 0.8609 | 0.7956 | 0.8476 | 0.8578 | |
|
| No log | 8.0 | 192 | 0.3106 | 0.8574 | 0.7836 | 0.8401 | 0.8509 | |
|
| No log | 9.0 | 216 | 0.3054 | 0.8532 | 0.7857 | 0.8378 | 0.8481 | |
|
| No log | 10.0 | 240 | 0.3136 | 0.8455 | 0.7789 | 0.8282 | 0.8432 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.25.1 |
|
- Pytorch 1.12.1 |
|
- Datasets 2.5.1 |
|
- Tokenizers 0.12.1 |
