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TED_CLM_gpt2_tedlium2
Lakoc/TED_CLM_gpt2_tedlium2
TED_CLM_gpt2_tedlium2 is a text generation model from Lakoc. Use it when you need the model to write or continue text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Generation
- Library
- transformers
- Model type
- gpt2
- Access
- Public
- Created
- Oct 30, 2023
- Updated
- Oct 31, 2023
- SHA
- 1a9beab7
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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_tedlium2
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8951
- Accuracy: 0.5484
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 |
|---|---|---|---|---|
| 2.1528 | 0.62 | 3000 | 2.3612 | 0.4554 |
| 1.9797 | 1.24 | 6000 | 2.2025 | 0.4923 |
| 1.9185 | 1.86 | 9000 | 2.1189 | 0.5089 |
| 1.8816 | 2.49 | 12000 | 2.0701 | 0.5168 |
| 1.8524 | 3.11 | 15000 | 2.0396 | 0.5232 |
| 1.8388 | 3.73 | 18000 | 2.0113 | 0.5259 |
| 1.8223 | 4.35 | 21000 | 1.9935 | 0.5307 |
| 1.8051 | 4.97 | 24000 | 1.9729 | 0.5332 |
| 1.7875 | 5.59 | 27000 | 1.9588 | 0.5344 |
| 1.7709 | 6.22 | 30000 | 1.9441 | 0.5369 |
| 1.7643 | 6.84 | 33000 | 1.9461 | 0.5381 |
| 1.7567 | 7.46 | 36000 | 1.9471 | 0.5395 |
| 1.7482 | 8.08 | 39000 | 1.9307 | 0.5412 |
| 1.7399 | 8.7 | 42000 | 1.9308 | 0.5415 |
| 1.7303 | 9.32 | 45000 | 1.9262 | 0.5419 |
| 1.7353 | 9.94 | 48000 | 1.9257 | 0.5434 |
| 1.7267 | 10.57 | 51000 | 1.9181 | 0.5453 |
| 1.719 | 11.19 | 54000 | 1.9204 | 0.5443 |
| 1.716 | 11.81 | 57000 | 1.9073 | 0.5473 |
| 1.7072 | 12.43 | 60000 | 1.9051 | 0.5465 |
| 1.7093 | 13.05 | 63000 | 1.9001 | 0.5490 |
| 1.708 | 13.67 | 66000 | 1.8998 | 0.5483 |
| 1.6972 | 14.29 | 69000 | 1.8968 | 0.5489 |
| 1.7001 | 14.92 | 72000 | 1.8951 | 0.5484 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Generation
- Library
- transformers
- Type
- gpt2
- Created
- Oct 30, 2023
- Updated
- Oct 31, 2023