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flan-t5-large-finetuned-coding_instructions_2023_08_18__12_06
jerome1519/flan-t5-large-finetuned-coding_instructions_2023_08_18__12_06
flan-t5-large-finetuned-coding_instructions_2023_08_18__12_06 is a machine learning model from jerome1519. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Aug 18, 2023
- Updated
- Aug 18, 2023
- SHA
- ebd5cf8f
Base models
Model card
From the Hugging Face model README
<!-- 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-large-finetuned-coding_instructions_2023_08_18__12_06
This model is a fine-tuned version of google/flan-t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6230
- Rouge1: 47.0864
- Rouge2: 31.2968
- Rougel: 45.9675
- Rougelsum: 46.0612
- Gen Len: 19.0
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 10 | 0.9891 | 18.047 | 9.6197 | 18.1466 | 18.2622 | 16.9538 |
| No log | 2.0 | 20 | 0.7803 | 21.724 | 12.8839 | 21.4666 | 21.6773 | 17.7385 |
| No log | 3.0 | 30 | 0.6827 | 42.1883 | 27.0064 | 41.5285 | 41.6611 | 18.9077 |
| No log | 4.0 | 40 | 0.6526 | 44.8257 | 28.8931 | 43.8323 | 43.7858 | 18.9846 |
| No log | 5.0 | 50 | 0.6407 | 44.6781 | 29.5477 | 43.9053 | 43.8475 | 19.0 |
| No log | 6.0 | 60 | 0.6334 | 46.039 | 31.3315 | 45.3508 | 45.3701 | 19.0 |
| No log | 7.0 | 70 | 0.6281 | 46.8592 | 31.2186 | 46.1283 | 46.1169 | 19.0 |
| No log | 8.0 | 80 | 0.6250 | 46.5201 | 30.8844 | 45.5541 | 45.6876 | 19.0 |
| No log | 9.0 | 90 | 0.6236 | 47.074 | 31.2968 | 46.1336 | 46.258 | 19.0 |
| No log | 10.0 | 100 | 0.6230 | 47.0864 | 31.2968 | 45.9675 | 46.0612 | 19.0 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Aug 18, 2023
- Updated
- Aug 18, 2023