File size: 2,256 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 |
---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: flan_t5_base_scotus
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_scotus
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: 1.6815
- Accuracy: 0.5057
- F1 Macro: 0.2620
- F1 Micro: 0.5057
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.9501 | 0.32 | 50 | 1.8292 | 0.4321 | 0.1494 | 0.4321 |
| 1.6556 | 0.64 | 100 | 1.8077 | 0.475 | 0.2243 | 0.475 |
| 1.8655 | 0.96 | 150 | 1.8138 | 0.485 | 0.2288 | 0.485 |
| 1.7747 | 1.27 | 200 | 1.8271 | 0.4671 | 0.2230 | 0.4671 |
| 1.6466 | 1.59 | 250 | 1.8139 | 0.4771 | 0.2300 | 0.4771 |
| 1.5496 | 1.91 | 300 | 1.7897 | 0.4793 | 0.2333 | 0.4793 |
| 1.5551 | 2.23 | 350 | 1.7017 | 0.4993 | 0.2513 | 0.4993 |
| 1.463 | 2.55 | 400 | 1.6897 | 0.505 | 0.2606 | 0.505 |
| 1.4005 | 2.87 | 450 | 1.6815 | 0.5057 | 0.2620 | 0.5057 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|