File size: 3,348 Bytes
aa5b5e2 |
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 76 77 78 79 80 81 82 83 84 85 86 87 88 |
---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: flan_t5_base_amazon
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. -->
# flan_t5_base_amazon
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5448
- Accuracy: 0.8412
- F1 Macro: 0.8142
- F1 Micro: 0.8412
## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.1669 | 0.13 | 50 | 0.9142 | 0.7404 | 0.6916 | 0.7404 |
| 0.8536 | 0.26 | 100 | 0.8417 | 0.7569 | 0.7197 | 0.7569 |
| 0.827 | 0.39 | 150 | 0.6893 | 0.7905 | 0.7471 | 0.7905 |
| 0.672 | 0.53 | 200 | 0.7235 | 0.7984 | 0.7730 | 0.7984 |
| 0.7424 | 0.66 | 250 | 0.6684 | 0.7945 | 0.7461 | 0.7945 |
| 0.6802 | 0.79 | 300 | 0.6008 | 0.8215 | 0.8014 | 0.8215 |
| 0.7847 | 0.92 | 350 | 0.6225 | 0.8123 | 0.7925 | 0.8123 |
| 0.5258 | 1.05 | 400 | 0.6656 | 0.8215 | 0.8000 | 0.8215 |
| 0.4945 | 1.18 | 450 | 0.6410 | 0.8235 | 0.7983 | 0.8235 |
| 0.4097 | 1.32 | 500 | 0.5937 | 0.8347 | 0.8110 | 0.8347 |
| 0.4116 | 1.45 | 550 | 0.5966 | 0.8314 | 0.8061 | 0.8314 |
| 0.4785 | 1.58 | 600 | 0.5696 | 0.8347 | 0.8107 | 0.8347 |
| 0.4821 | 1.71 | 650 | 0.5536 | 0.8366 | 0.8098 | 0.8366 |
| 0.4137 | 1.84 | 700 | 0.5612 | 0.8373 | 0.8116 | 0.8373 |
| 0.4623 | 1.97 | 750 | 0.5448 | 0.8412 | 0.8142 | 0.8412 |
| 0.1953 | 2.11 | 800 | 0.5984 | 0.8472 | 0.8201 | 0.8472 |
| 0.2114 | 2.24 | 850 | 0.6189 | 0.8432 | 0.8177 | 0.8432 |
| 0.2252 | 2.37 | 900 | 0.6411 | 0.8465 | 0.8199 | 0.8465 |
| 0.1937 | 2.5 | 950 | 0.6044 | 0.8524 | 0.8245 | 0.8524 |
| 0.2611 | 2.63 | 1000 | 0.6188 | 0.8472 | 0.8189 | 0.8472 |
| 0.3021 | 2.76 | 1050 | 0.6018 | 0.8472 | 0.8189 | 0.8472 |
| 0.2309 | 2.89 | 1100 | 0.5804 | 0.8478 | 0.8186 | 0.8478 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|