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medusa-1.0-ELYZA-japanese-Llama-2-7b-instruct
This model is a fine-tuned version of elyza/ELYZA-japanese-Llama-2-7b-instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8838
Model description
This is a Medusa-1 created using Medusa.
Intended uses & limitations
Training and evaluation data
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 40
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.4268 | 0.06 | 40 | 2.4129 |
2.204 | 0.11 | 80 | 2.2328 |
2.1341 | 0.17 | 120 | 2.1939 |
2.1774 | 0.23 | 160 | 2.1762 |
2.1331 | 0.28 | 200 | 2.1652 |
2.1485 | 0.34 | 240 | 2.1537 |
2.1608 | 0.4 | 280 | 2.1485 |
2.0998 | 0.45 | 320 | 2.1340 |
2.1478 | 0.51 | 360 | 2.1233 |
2.1374 | 0.57 | 400 | 2.1165 |
2.0657 | 0.62 | 440 | 2.0984 |
2.1227 | 0.68 | 480 | 2.0834 |
2.0573 | 0.74 | 520 | 2.0739 |
2.0501 | 0.79 | 560 | 2.0602 |
2.0664 | 0.85 | 600 | 2.0431 |
2.0231 | 0.91 | 640 | 2.0277 |
2.0263 | 0.96 | 680 | 2.0119 |
1.8635 | 1.02 | 720 | 1.9990 |
1.8844 | 1.07 | 760 | 1.9905 |
1.8585 | 1.13 | 800 | 1.9796 |
1.8018 | 1.19 | 840 | 1.9728 |
1.8134 | 1.24 | 880 | 1.9595 |
1.7795 | 1.3 | 920 | 1.9498 |
1.7603 | 1.36 | 960 | 1.9371 |
1.8302 | 1.41 | 1000 | 1.9262 |
1.7909 | 1.47 | 1040 | 1.9172 |
1.7787 | 1.53 | 1080 | 1.9083 |
1.7476 | 1.58 | 1120 | 1.9010 |
1.7897 | 1.64 | 1160 | 1.8945 |
1.7795 | 1.7 | 1200 | 1.8895 |
1.7329 | 1.75 | 1240 | 1.8864 |
1.7221 | 1.81 | 1280 | 1.8846 |
1.7624 | 1.87 | 1320 | 1.8840 |
1.793 | 1.92 | 1360 | 1.8838 |
1.7839 | 1.98 | 1400 | 1.8838 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.14.1
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Base model
elyza/ELYZA-japanese-Llama-2-7b-instruct