cem13/complaint_to_sythoms_mix_8x7b
Browse files- README.md +235 -0
- adapter_config.json +35 -0
- adapter_model.safetensors +3 -0
- runs/Aug12_07-24-44_9bcd5dae9cf3/events.out.tfevents.1723447489.9bcd5dae9cf3.1307.0 +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
- training_args.bin +3 -0
README.md
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1 |
+
---
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+
base_model: mistralai/Mixtral-8x7B-v0.1
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datasets:
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- generator
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library_name: peft
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license: apache-2.0
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tags:
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+
- trl
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- sft
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- generated_from_trainer
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model-index:
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- name: Mixtral_Alpace_v2
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+
results: []
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+
---
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15 |
+
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+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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+
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+
# Mixtral_Alpace_v2
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+
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+
This model is a fine-tuned version of [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) on the generator dataset.
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+
It achieves the following results on the evaluation set:
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+
- Loss: 0.5881
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+
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+
## Model description
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+
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More information needed
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+
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## Intended uses & limitations
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+
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+
More information needed
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+
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+
## Training and evaluation data
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+
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+
More information needed
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+
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## Training procedure
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+
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+
### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2.5e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 15
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- num_epochs: 15
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+
### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-------:|:----:|:---------------:|
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| 1.5291 | 0.0870 | 10 | 1.6326 |
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| 1.58 | 0.1739 | 20 | 1.5665 |
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| 1.4109 | 0.2609 | 30 | 1.4856 |
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| 1.4493 | 0.3478 | 40 | 1.4159 |
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| 1.2503 | 0.4348 | 50 | 1.3493 |
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| 1.2441 | 0.5217 | 60 | 1.2719 |
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| 1.1923 | 0.6087 | 70 | 1.1930 |
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| 1.1158 | 0.6957 | 80 | 1.1193 |
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| 1.0184 | 0.7826 | 90 | 1.0541 |
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| 1.0231 | 0.8696 | 100 | 1.0056 |
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| 0.9731 | 0.9565 | 110 | 0.9619 |
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| 0.892 | 1.0435 | 120 | 0.9170 |
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| 0.911 | 1.1304 | 130 | 0.8727 |
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| 0.7789 | 1.2174 | 140 | 0.8338 |
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| 0.8049 | 1.3043 | 150 | 0.8041 |
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| 0.7691 | 1.3913 | 160 | 0.7788 |
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| 0.7869 | 1.4783 | 170 | 0.7589 |
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| 0.7366 | 1.5652 | 180 | 0.7428 |
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| 0.7436 | 1.6522 | 190 | 0.7282 |
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| 0.7271 | 1.7391 | 200 | 0.7157 |
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| 0.6809 | 1.8261 | 210 | 0.7056 |
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| 0.7068 | 1.9130 | 220 | 0.6960 |
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| 0.6446 | 2.0 | 230 | 0.6872 |
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| 0.6682 | 2.0870 | 240 | 0.6819 |
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| 0.7003 | 2.1739 | 250 | 0.6745 |
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| 0.6859 | 2.2609 | 260 | 0.6701 |
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| 0.6169 | 2.3478 | 270 | 0.6655 |
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| 0.666 | 2.4348 | 280 | 0.6607 |
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| 0.6325 | 2.5217 | 290 | 0.6575 |
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| 0.6408 | 2.6087 | 300 | 0.6536 |
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| 0.6371 | 2.6957 | 310 | 0.6507 |
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| 0.5933 | 2.7826 | 320 | 0.6474 |
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| 0.6313 | 2.8696 | 330 | 0.6450 |
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| 0.6453 | 2.9565 | 340 | 0.6421 |
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| 0.6807 | 3.0435 | 350 | 0.6407 |
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| 0.6217 | 3.1304 | 360 | 0.6390 |
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| 0.589 | 3.2174 | 370 | 0.6355 |
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| 0.5591 | 3.3043 | 380 | 0.6337 |
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| 0.6818 | 3.3913 | 390 | 0.6319 |
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| 0.6269 | 3.4783 | 400 | 0.6306 |
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| 0.611 | 3.5652 | 410 | 0.6286 |
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| 0.5602 | 3.6522 | 420 | 0.6268 |
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| 0.6735 | 3.7391 | 430 | 0.6251 |
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| 0.5269 | 3.8261 | 440 | 0.6246 |
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| 0.6109 | 3.9130 | 450 | 0.6232 |
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| 0.5745 | 4.0 | 460 | 0.6221 |
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| 0.6348 | 4.0870 | 470 | 0.6227 |
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| 0.5398 | 4.1739 | 480 | 0.6203 |
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| 0.6145 | 4.2609 | 490 | 0.6194 |
|
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| 0.621 | 4.3478 | 500 | 0.6178 |
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| 0.6123 | 4.4348 | 510 | 0.6172 |
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| 0.6113 | 4.5217 | 520 | 0.6162 |
|
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| 0.5991 | 4.6087 | 530 | 0.6154 |
|
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| 0.5244 | 4.6957 | 540 | 0.6143 |
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| 0.5832 | 4.7826 | 550 | 0.6136 |
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| 0.6284 | 4.8696 | 560 | 0.6120 |
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| 0.54 | 4.9565 | 570 | 0.6121 |
|
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| 0.541 | 5.0435 | 580 | 0.6120 |
|
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| 0.5204 | 5.1304 | 590 | 0.6108 |
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| 0.5961 | 5.2174 | 600 | 0.6101 |
|
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| 0.5522 | 5.3043 | 610 | 0.6098 |
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| 0.5778 | 5.3913 | 620 | 0.6087 |
|
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| 0.6059 | 5.4783 | 630 | 0.6090 |
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| 0.5852 | 5.5652 | 640 | 0.6085 |
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| 0.5687 | 5.6522 | 650 | 0.6072 |
|
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| 0.5685 | 5.7391 | 660 | 0.6061 |
|
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| 0.593 | 5.8261 | 670 | 0.6052 |
|
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| 0.5975 | 5.9130 | 680 | 0.6055 |
|
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| 0.5489 | 6.0 | 690 | 0.6047 |
|
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| 0.567 | 6.0870 | 700 | 0.6049 |
|
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| 0.5706 | 6.1739 | 710 | 0.6035 |
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| 0.658 | 6.2609 | 720 | 0.6024 |
|
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| 0.559 | 6.3478 | 730 | 0.6023 |
|
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| 0.545 | 6.4348 | 740 | 0.6019 |
|
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| 0.6096 | 6.5217 | 750 | 0.6021 |
|
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| 0.5385 | 6.6087 | 760 | 0.6018 |
|
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| 0.5505 | 6.6957 | 770 | 0.6012 |
|
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| 0.5058 | 6.7826 | 780 | 0.6003 |
|
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| 0.5899 | 6.8696 | 790 | 0.5999 |
|
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| 0.5102 | 6.9565 | 800 | 0.5995 |
|
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+
| 0.5185 | 7.0435 | 810 | 0.5995 |
|
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| 0.5055 | 7.1304 | 820 | 0.5991 |
|
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| 0.5907 | 7.2174 | 830 | 0.5997 |
|
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| 0.5636 | 7.3043 | 840 | 0.5991 |
|
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| 0.5505 | 7.3913 | 850 | 0.5986 |
|
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| 0.5621 | 7.4783 | 860 | 0.5977 |
|
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| 0.4968 | 7.5652 | 870 | 0.5976 |
|
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| 0.5713 | 7.6522 | 880 | 0.5970 |
|
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+
| 0.5968 | 7.7391 | 890 | 0.5970 |
|
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| 0.531 | 7.8261 | 900 | 0.5964 |
|
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| 0.538 | 7.9130 | 910 | 0.5959 |
|
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| 0.6087 | 8.0 | 920 | 0.5959 |
|
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| 0.5845 | 8.0870 | 930 | 0.5963 |
|
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| 0.5197 | 8.1739 | 940 | 0.5960 |
|
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+
| 0.5128 | 8.2609 | 950 | 0.5959 |
|
150 |
+
| 0.5613 | 8.3478 | 960 | 0.5956 |
|
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+
| 0.5268 | 8.4348 | 970 | 0.5953 |
|
152 |
+
| 0.5696 | 8.5217 | 980 | 0.5952 |
|
153 |
+
| 0.5755 | 8.6087 | 990 | 0.5941 |
|
154 |
+
| 0.5014 | 8.6957 | 1000 | 0.5945 |
|
155 |
+
| 0.5568 | 8.7826 | 1010 | 0.5936 |
|
156 |
+
| 0.5934 | 8.8696 | 1020 | 0.5944 |
|
157 |
+
| 0.5178 | 8.9565 | 1030 | 0.5941 |
|
158 |
+
| 0.4618 | 9.0435 | 1040 | 0.5936 |
|
159 |
+
| 0.4867 | 9.1304 | 1050 | 0.5934 |
|
160 |
+
| 0.5402 | 9.2174 | 1060 | 0.5937 |
|
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+
| 0.5177 | 9.3043 | 1070 | 0.5936 |
|
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+
| 0.5825 | 9.3913 | 1080 | 0.5926 |
|
163 |
+
| 0.5523 | 9.4783 | 1090 | 0.5929 |
|
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+
| 0.583 | 9.5652 | 1100 | 0.5920 |
|
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+
| 0.5232 | 9.6522 | 1110 | 0.5927 |
|
166 |
+
| 0.5367 | 9.7391 | 1120 | 0.5920 |
|
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+
| 0.5321 | 9.8261 | 1130 | 0.5913 |
|
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+
| 0.5672 | 9.9130 | 1140 | 0.5910 |
|
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| 0.5549 | 10.0 | 1150 | 0.5910 |
|
170 |
+
| 0.5191 | 10.0870 | 1160 | 0.5915 |
|
171 |
+
| 0.5463 | 10.1739 | 1170 | 0.5915 |
|
172 |
+
| 0.5275 | 10.2609 | 1180 | 0.5913 |
|
173 |
+
| 0.5484 | 10.3478 | 1190 | 0.5915 |
|
174 |
+
| 0.5293 | 10.4348 | 1200 | 0.5910 |
|
175 |
+
| 0.519 | 10.5217 | 1210 | 0.5903 |
|
176 |
+
| 0.5129 | 10.6087 | 1220 | 0.5898 |
|
177 |
+
| 0.5793 | 10.6957 | 1230 | 0.5900 |
|
178 |
+
| 0.4481 | 10.7826 | 1240 | 0.5901 |
|
179 |
+
| 0.5309 | 10.8696 | 1250 | 0.5903 |
|
180 |
+
| 0.5887 | 10.9565 | 1260 | 0.5898 |
|
181 |
+
| 0.5109 | 11.0435 | 1270 | 0.5907 |
|
182 |
+
| 0.5776 | 11.1304 | 1280 | 0.5902 |
|
183 |
+
| 0.4984 | 11.2174 | 1290 | 0.5898 |
|
184 |
+
| 0.5656 | 11.3043 | 1300 | 0.5898 |
|
185 |
+
| 0.4931 | 11.3913 | 1310 | 0.5902 |
|
186 |
+
| 0.531 | 11.4783 | 1320 | 0.5900 |
|
187 |
+
| 0.5163 | 11.5652 | 1330 | 0.5892 |
|
188 |
+
| 0.5314 | 11.6522 | 1340 | 0.5894 |
|
189 |
+
| 0.4766 | 11.7391 | 1350 | 0.5893 |
|
190 |
+
| 0.5201 | 11.8261 | 1360 | 0.5896 |
|
191 |
+
| 0.6127 | 11.9130 | 1370 | 0.5889 |
|
192 |
+
| 0.5441 | 12.0 | 1380 | 0.5888 |
|
193 |
+
| 0.5258 | 12.0870 | 1390 | 0.5894 |
|
194 |
+
| 0.5722 | 12.1739 | 1400 | 0.5887 |
|
195 |
+
| 0.5228 | 12.2609 | 1410 | 0.5891 |
|
196 |
+
| 0.524 | 12.3478 | 1420 | 0.5884 |
|
197 |
+
| 0.4951 | 12.4348 | 1430 | 0.5894 |
|
198 |
+
| 0.5235 | 12.5217 | 1440 | 0.5893 |
|
199 |
+
| 0.5071 | 12.6087 | 1450 | 0.5889 |
|
200 |
+
| 0.5417 | 12.6957 | 1460 | 0.5886 |
|
201 |
+
| 0.4882 | 12.7826 | 1470 | 0.5889 |
|
202 |
+
| 0.548 | 12.8696 | 1480 | 0.5889 |
|
203 |
+
| 0.529 | 12.9565 | 1490 | 0.5889 |
|
204 |
+
| 0.5646 | 13.0435 | 1500 | 0.5887 |
|
205 |
+
| 0.5142 | 13.1304 | 1510 | 0.5889 |
|
206 |
+
| 0.5161 | 13.2174 | 1520 | 0.5886 |
|
207 |
+
| 0.5008 | 13.3043 | 1530 | 0.5888 |
|
208 |
+
| 0.5187 | 13.3913 | 1540 | 0.5887 |
|
209 |
+
| 0.5334 | 13.4783 | 1550 | 0.5886 |
|
210 |
+
| 0.5099 | 13.5652 | 1560 | 0.5884 |
|
211 |
+
| 0.5644 | 13.6522 | 1570 | 0.5888 |
|
212 |
+
| 0.5242 | 13.7391 | 1580 | 0.5882 |
|
213 |
+
| 0.4912 | 13.8261 | 1590 | 0.5886 |
|
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+
| 0.5459 | 13.9130 | 1600 | 0.5884 |
|
215 |
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| 0.5204 | 14.0 | 1610 | 0.5881 |
|
216 |
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| 0.4644 | 14.0870 | 1620 | 0.5884 |
|
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| 0.5364 | 14.1739 | 1630 | 0.5885 |
|
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+
| 0.5852 | 14.2609 | 1640 | 0.5887 |
|
219 |
+
| 0.5135 | 14.3478 | 1650 | 0.5884 |
|
220 |
+
| 0.5192 | 14.4348 | 1660 | 0.5885 |
|
221 |
+
| 0.5093 | 14.5217 | 1670 | 0.5880 |
|
222 |
+
| 0.5398 | 14.6087 | 1680 | 0.5884 |
|
223 |
+
| 0.469 | 14.6957 | 1690 | 0.5882 |
|
224 |
+
| 0.5163 | 14.7826 | 1700 | 0.5883 |
|
225 |
+
| 0.5165 | 14.8696 | 1710 | 0.5883 |
|
226 |
+
| 0.5441 | 14.9565 | 1720 | 0.5881 |
|
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+
|
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+
|
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### Framework versions
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|
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- PEFT 0.12.0
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- Transformers 4.44.0
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- Pytorch 2.4.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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adapter_config.json
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