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TED_CLM_gpt2_tedlium_additional_head
Lakoc/TED_CLM_gpt2_tedlium_additional_head
TED_CLM_gpt2_tedlium_additional_head is a machine learning model from Lakoc. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- gpt2-multi-head
- Access
- Public
- Created
- Nov 1, 2023
- Updated
- Nov 1, 2023
- SHA
- 9ea4f149
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. -->
TED_CLM_gpt2_tedlium_additional_head
This model is a fine-tuned version of Lakoc/gpt2_512h_16l_add_head8 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9139
- Accuracy: 0.5529
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: 0.001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 512
- total_eval_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20000
- num_epochs: 15.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2945 | 0.62 | 3000 | 2.4760 | 0.4352 |
| 2.0669 | 1.24 | 6000 | 2.2729 | 0.4767 |
| 1.9754 | 1.86 | 9000 | 2.1827 | 0.4974 |
| 1.9292 | 2.49 | 12000 | 2.1086 | 0.5139 |
| 1.8983 | 3.11 | 15000 | 2.0666 | 0.5223 |
| 1.8853 | 3.73 | 18000 | 2.0389 | 0.5278 |
| 1.8708 | 4.35 | 21000 | 2.0216 | 0.5301 |
| 1.8524 | 4.97 | 24000 | 2.0024 | 0.5352 |
| 1.836 | 5.59 | 27000 | 1.9915 | 0.5365 |
| 1.8219 | 6.22 | 30000 | 1.9847 | 0.5410 |
| 1.8134 | 6.84 | 33000 | 1.9670 | 0.5408 |
| 1.8088 | 7.46 | 36000 | 1.9736 | 0.5425 |
| 1.8011 | 8.08 | 39000 | 1.9610 | 0.5426 |
| 1.7901 | 8.7 | 42000 | 1.9519 | 0.5459 |
| 1.7829 | 9.32 | 45000 | 1.9524 | 0.5463 |
| 1.7865 | 9.94 | 48000 | 1.9424 | 0.5479 |
| 1.7775 | 10.57 | 51000 | 1.9421 | 0.5480 |
| 1.7698 | 11.19 | 54000 | 1.9346 | 0.5486 |
| 1.767 | 11.81 | 57000 | 1.9249 | 0.5493 |
| 1.7578 | 12.43 | 60000 | 1.9262 | 0.5500 |
| 1.7613 | 13.05 | 63000 | 1.9185 | 0.5508 |
| 1.7591 | 13.67 | 66000 | 1.9191 | 0.5523 |
| 1.7489 | 14.29 | 69000 | 1.9159 | 0.5522 |
| 1.7506 | 14.92 | 72000 | 1.9139 | 0.5529 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.13.3
- Library
- transformers
- Type
- gpt2-multi-head
- Created
- Nov 1, 2023
- Updated
- Nov 1, 2023