update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,74 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: VK246/IC_ver6d_coco_swin_gpt2_50Bpc_1e
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
datasets:
|
| 6 |
+
- coco
|
| 7 |
+
metrics:
|
| 8 |
+
- rouge
|
| 9 |
+
model-index:
|
| 10 |
+
- name: IC_ver6e_coco_swin_gpt2_50Apc_1e
|
| 11 |
+
results: []
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
+
|
| 17 |
+
# IC_ver6e_coco_swin_gpt2_50Apc_1e
|
| 18 |
+
|
| 19 |
+
This model is a fine-tuned version of [VK246/IC_ver6d_coco_swin_gpt2_50Bpc_1e](https://huggingface.co/VK246/IC_ver6d_coco_swin_gpt2_50Bpc_1e) on the coco dataset.
|
| 20 |
+
It achieves the following results on the evaluation set:
|
| 21 |
+
- Loss: 0.7783
|
| 22 |
+
- Cider: 19.1116
|
| 23 |
+
- Rouge1: 42.2076
|
| 24 |
+
- Rouge2: 16.6791
|
| 25 |
+
- Rougel: 38.4352
|
| 26 |
+
- Rougelsum: 38.4324
|
| 27 |
+
- Bleu-1: 42.9768
|
| 28 |
+
- Bleu-2: 25.0535
|
| 29 |
+
- Bleu-3: 15.8932
|
| 30 |
+
- Bleu-4: 10.5581
|
| 31 |
+
- Gen Len: 11.2806
|
| 32 |
+
|
| 33 |
+
## Model description
|
| 34 |
+
|
| 35 |
+
More information needed
|
| 36 |
+
|
| 37 |
+
## Intended uses & limitations
|
| 38 |
+
|
| 39 |
+
More information needed
|
| 40 |
+
|
| 41 |
+
## Training and evaluation data
|
| 42 |
+
|
| 43 |
+
More information needed
|
| 44 |
+
|
| 45 |
+
## Training procedure
|
| 46 |
+
|
| 47 |
+
### Training hyperparameters
|
| 48 |
+
|
| 49 |
+
The following hyperparameters were used during training:
|
| 50 |
+
- learning_rate: 5e-05
|
| 51 |
+
- train_batch_size: 96
|
| 52 |
+
- eval_batch_size: 96
|
| 53 |
+
- seed: 42
|
| 54 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 55 |
+
- lr_scheduler_type: linear
|
| 56 |
+
- num_epochs: 1
|
| 57 |
+
|
| 58 |
+
### Training results
|
| 59 |
+
|
| 60 |
+
| Training Loss | Epoch | Step | Validation Loss | Cider | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Gen Len |
|
| 61 |
+
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:-------:|:-------:|:-------:|
|
| 62 |
+
| 0.7299 | 0.17 | 500 | 0.8169 | 15.1223 | 40.4746 | 15.1013 | 36.817 | 36.8166 | 41.7335 | 23.5713 | 14.621 | 9.566 | 11.2806 |
|
| 63 |
+
| 0.7243 | 0.34 | 1000 | 0.8063 | 15.7288 | 41.2081 | 15.8926 | 37.4018 | 37.4016 | 42.2656 | 24.2595 | 15.2602 | 10.0788 | 11.2806 |
|
| 64 |
+
| 0.7396 | 0.51 | 1500 | 0.7999 | 15.5164 | 41.6231 | 16.1665 | 38.0103 | 38.0119 | 42.0958 | 24.3223 | 15.2851 | 10.0869 | 11.2806 |
|
| 65 |
+
| 0.7507 | 0.68 | 2000 | 0.7879 | 15.3421 | 41.9871 | 16.4909 | 38.2491 | 38.2515 | 42.6606 | 24.7464 | 15.6329 | 10.3731 | 11.2806 |
|
| 66 |
+
| 0.7712 | 0.85 | 2500 | 0.7820 | 11.751 | 41.9906 | 16.5153 | 38.2624 | 38.2634 | 42.8539 | 24.8663 | 15.7151 | 10.3989 | 11.2806 |
|
| 67 |
+
|
| 68 |
+
|
| 69 |
+
### Framework versions
|
| 70 |
+
|
| 71 |
+
- Transformers 4.31.0
|
| 72 |
+
- Pytorch 2.0.1+cu118
|
| 73 |
+
- Datasets 2.14.4
|
| 74 |
+
- Tokenizers 0.13.3
|