models
This model is a fine-tuned version of Salesforce/blip-image-captioning-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.4107
- Wer Score: 0.5495
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Score |
---|---|---|---|---|
9.4536 | 0.05 | 10 | 7.8217 | 41.7753 |
7.3267 | 0.11 | 20 | 6.6585 | 0.7753 |
6.2358 | 0.16 | 30 | 5.7758 | 0.5667 |
5.2862 | 0.22 | 40 | 4.7628 | 0.5419 |
4.3786 | 0.27 | 50 | 3.9203 | 0.6398 |
3.5554 | 0.33 | 60 | 3.1482 | 0.5613 |
2.849 | 0.38 | 70 | 2.5209 | 0.5548 |
2.3041 | 0.44 | 80 | 2.0561 | 0.5645 |
1.8999 | 0.49 | 90 | 1.7474 | 0.5645 |
1.658 | 0.55 | 100 | 1.5722 | 0.5548 |
1.5238 | 0.6 | 110 | 1.4836 | 0.5591 |
1.4726 | 0.66 | 120 | 1.4461 | 0.5538 |
1.4328 | 0.71 | 130 | 1.4285 | 0.5473 |
1.4211 | 0.77 | 140 | 1.4205 | 0.5559 |
1.4202 | 0.82 | 150 | 1.4156 | 0.5548 |
1.4098 | 0.88 | 160 | 1.4129 | 0.5505 |
1.4124 | 0.93 | 170 | 1.4113 | 0.5548 |
1.4075 | 0.99 | 180 | 1.4107 | 0.5495 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cpu
- Datasets 2.13.1
- Tokenizers 0.13.3
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