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pp-mod-subj-lstm-2
CLMBR/pp-mod-subj-lstm-2
pp-mod-subj-lstm-2 is a machine learning model from CLMBR. 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
- rnn
- Access
- Public
- Created
- Jan 26, 2024
- Updated
- Feb 2, 2024
- SHA
- d411b56d
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. -->
pp-mod-subj2-lstm-2
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.0244
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: 32
- eval_batch_size: 32
- seed: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3052726
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.7935 | 0.03 | 76320 | 4.8062 |
| 4.5109 | 1.03 | 152640 | 4.5276 |
| 4.364 | 0.03 | 228960 | 4.3927 |
| 4.2769 | 1.03 | 305280 | 4.3088 |
| 4.218 | 2.03 | 381600 | 4.2524 |
| 4.1632 | 0.03 | 457920 | 4.2110 |
| 4.122 | 1.03 | 534240 | 4.1790 |
| 4.0898 | 0.03 | 610560 | 4.1564 |
| 4.061 | 1.03 | 686880 | 4.1367 |
| 4.0412 | 0.03 | 763200 | 4.1209 |
| 4.017 | 1.03 | 839520 | 4.1068 |
| 4.0005 | 2.03 | 915840 | 4.0968 |
| 3.9871 | 0.03 | 992160 | 4.0886 |
| 3.9741 | 1.03 | 1068480 | 4.0804 |
| 3.9581 | 0.03 | 1144800 | 4.0726 |
| 3.9422 | 1.03 | 1221120 | 4.0674 |
| 3.9348 | 2.03 | 1297440 | 4.0626 |
| 3.9277 | 0.03 | 1373760 | 4.0584 |
| 3.9161 | 1.03 | 1450080 | 4.0541 |
| 3.9137 | 2.03 | 1526400 | 4.0513 |
| 3.9114 | 0.03 | 1602720 | 4.0470 |
| 3.9006 | 1.03 | 1679040 | 4.0451 |
| 3.8935 | 2.03 | 1755360 | 4.0424 |
| 3.8884 | 0.03 | 1831680 | 4.0403 |
| 3.8812 | 1.03 | 1908000 | 4.0383 |
| 3.8775 | 0.03 | 1984320 | 4.0364 |
| 3.8699 | 1.03 | 2060640 | 4.0352 |
| 3.8649 | 0.03 | 2136960 | 4.0336 |
| 3.8632 | 1.03 | 2213280 | 4.0325 |
| 3.8588 | 0.03 | 2289600 | 4.0305 |
| 3.8516 | 1.03 | 2365920 | 4.0299 |
| 3.8467 | 2.03 | 2442240 | 4.0294 |
| 3.8464 | 0.03 | 2518560 | 4.0286 |
| 3.8457 | 0.03 | 2594880 | 4.0275 |
| 3.8392 | 1.03 | 2671200 | 4.0269 |
| 3.841 | 0.03 | 2747520 | 4.0259 |
| 3.8415 | 1.03 | 2823840 | 4.0257 |
| 3.8387 | 0.03 | 2900160 | 4.0253 |
| 3.8357 | 1.03 | 2976480 | 4.0248 |
| 3.834 | 2.02 | 3052726 | 4.0244 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- rnn
- Created
- Jan 26, 2024
- Updated
- Feb 2, 2024