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pp-mod-subj-lstm-1
CLMBR/pp-mod-subj-lstm-1
pp-mod-subj-lstm-1 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
- 96d91481
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-1
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: 1
- 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 |
|---|---|---|---|
| 4.7926 | 0.03 | 76320 | 4.8046 |
| 4.5099 | 1.03 | 152640 | 4.5258 |
| 4.3635 | 0.03 | 228960 | 4.3901 |
| 4.2771 | 1.03 | 305280 | 4.3076 |
| 4.2173 | 2.03 | 381600 | 4.2516 |
| 4.1646 | 0.03 | 457920 | 4.2105 |
| 4.1238 | 0.03 | 534240 | 4.1808 |
| 4.0899 | 1.03 | 610560 | 4.1562 |
| 4.0628 | 2.03 | 686880 | 4.1370 |
| 4.0419 | 0.03 | 763200 | 4.1217 |
| 4.0191 | 1.03 | 839520 | 4.1092 |
| 4.0021 | 2.03 | 915840 | 4.0979 |
| 3.9884 | 0.03 | 992160 | 4.0885 |
| 3.9743 | 1.03 | 1068480 | 4.0805 |
| 3.9592 | 2.03 | 1144800 | 4.0736 |
| 3.9441 | 0.03 | 1221120 | 4.0688 |
| 3.9355 | 1.03 | 1297440 | 4.0630 |
| 3.9289 | 2.03 | 1373760 | 4.0589 |
| 3.9175 | 0.03 | 1450080 | 4.0547 |
| 3.9141 | 1.03 | 1526400 | 4.0505 |
| 3.9112 | 2.03 | 1602720 | 4.0477 |
| 3.9007 | 0.03 | 1679040 | 4.0438 |
| 3.8939 | 1.03 | 1755360 | 4.0432 |
| 3.8858 | 0.03 | 1831680 | 4.0397 |
| 3.8795 | 1.03 | 1908000 | 4.0380 |
| 3.8776 | 0.03 | 1984320 | 4.0363 |
| 3.8692 | 1.03 | 2060640 | 4.0353 |
| 3.8658 | 0.03 | 2136960 | 4.0338 |
| 3.8636 | 1.03 | 2213280 | 4.0321 |
| 3.8603 | 0.03 | 2289600 | 4.0314 |
| 3.8524 | 1.03 | 2365920 | 4.0305 |
| 3.846 | 2.03 | 2442240 | 4.0297 |
| 3.8448 | 0.03 | 2518560 | 4.0285 |
| 3.8429 | 0.03 | 2594880 | 4.0275 |
| 3.8383 | 1.03 | 2671200 | 4.0271 |
| 3.8414 | 0.03 | 2747520 | 4.0266 |
| 3.8428 | 0.03 | 2823840 | 4.0259 |
| 3.8395 | 0.03 | 2900160 | 4.0253 |
| 3.8371 | 1.03 | 2976480 | 4.0248 |
| 3.8331 | 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