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dalyaff
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phi2-QA-Arabic-phi

PEFT
Safetensors
phi
Generated from Trainer
custom_code
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End of training

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Files changed (4) hide show
  1. README.md +32 -47
  2. adapter_config.json +2 -2
  3. adapter_model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -5,7 +5,7 @@ library_name: peft
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  tags:
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  - generated_from_trainer
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  datasets:
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- - khalidalt/tydiqa-goldp
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  base_model: microsoft/phi-2
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  model-index:
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  - name: phi-2
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # phi-2
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- This model is a fine-tuned version of [microsoftl](https://huggingface.co/microsoftl) on the khalidalt/tydiqa-goldp dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1016
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  ## Model description
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@@ -39,66 +39,51 @@ More information needed
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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: 1
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  - eval_batch_size: 8
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 4
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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: 5
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- - training_steps: 2000
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 1.7708 | 0.02 | 50 | 1.5184 |
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- | 1.4903 | 0.04 | 100 | 1.2735 |
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- | 1.3474 | 0.06 | 150 | 1.2167 |
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- | 1.3178 | 0.08 | 200 | 1.1864 |
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- | 1.2963 | 0.1 | 250 | 1.1750 |
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- | 1.2671 | 0.12 | 300 | 1.1676 |
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- | 1.2484 | 0.14 | 350 | 1.1597 |
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- | 1.2797 | 0.16 | 400 | 1.1546 |
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- | 1.3196 | 0.18 | 450 | 1.1495 |
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- | 1.2881 | 0.2 | 500 | 1.1435 |
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- | 1.2389 | 0.22 | 550 | 1.1416 |
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- | 1.2489 | 0.24 | 600 | 1.1371 |
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- | 1.2223 | 0.26 | 650 | 1.1339 |
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- | 1.2012 | 0.28 | 700 | 1.1307 |
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- | 1.2285 | 0.3 | 750 | 1.1285 |
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- | 1.255 | 0.32 | 800 | 1.1251 |
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- | 1.2739 | 0.34 | 850 | 1.1229 |
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- | 1.2412 | 0.36 | 900 | 1.1217 |
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- | 1.2094 | 0.38 | 950 | 1.1204 |
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- | 1.246 | 0.4 | 1000 | 1.1202 |
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- | 1.1737 | 0.42 | 1050 | 1.1161 |
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- | 1.2427 | 0.44 | 1100 | 1.1144 |
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- | 1.2235 | 0.46 | 1150 | 1.1131 |
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- | 1.2301 | 0.48 | 1200 | 1.1119 |
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- | 1.1854 | 0.5 | 1250 | 1.1111 |
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- | 1.1949 | 0.52 | 1300 | 1.1094 |
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- | 1.243 | 0.54 | 1350 | 1.1088 |
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- | 1.2121 | 0.56 | 1400 | 1.1081 |
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- | 1.2124 | 0.58 | 1450 | 1.1081 |
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- | 1.2065 | 0.6 | 1500 | 1.1061 |
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- | 1.2357 | 0.62 | 1550 | 1.1058 |
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- | 1.2253 | 0.64 | 1600 | 1.1050 |
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- | 1.1751 | 0.66 | 1650 | 1.1034 |
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- | 1.2171 | 0.68 | 1700 | 1.1042 |
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- | 1.2091 | 0.7 | 1750 | 1.1038 |
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- | 1.2111 | 0.72 | 1800 | 1.1027 |
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- | 1.1808 | 0.74 | 1850 | 1.1023 |
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- | 1.1233 | 0.76 | 1900 | 1.1020 |
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- | 1.2327 | 0.78 | 1950 | 1.1020 |
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- | 1.1534 | 0.8 | 2000 | 1.1016 |
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  ### Framework versions
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  - PEFT 0.7.2.dev0
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- - Transformers 4.37.0.dev0
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.16.1
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  - Tokenizers 0.15.0
 
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  tags:
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  - generated_from_trainer
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  datasets:
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+ - dalyaff/darebah
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  base_model: microsoft/phi-2
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  model-index:
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  - name: phi-2
 
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  # phi-2
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+ This model is a fine-tuned version of [microsoftl](https://huggingface.co/microsoftl) on the dalyaff/darebah dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7778
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  ## Model description
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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: 2
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  - eval_batch_size: 8
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  - seed: 42
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  - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 8
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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: 5
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+ - training_steps: 2500
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.1134 | 0.89 | 100 | 1.0092 |
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+ | 0.8768 | 1.78 | 200 | 0.8800 |
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+ | 0.7644 | 2.67 | 300 | 0.8329 |
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+ | 0.7516 | 3.56 | 400 | 0.8081 |
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+ | 0.6618 | 4.44 | 500 | 0.7909 |
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+ | 0.6373 | 5.33 | 600 | 0.7845 |
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+ | 0.6154 | 6.22 | 700 | 0.7688 |
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+ | 0.6056 | 7.11 | 800 | 0.7716 |
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+ | 0.5719 | 8.0 | 900 | 0.7662 |
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+ | 0.5575 | 8.89 | 1000 | 0.7700 |
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+ | 0.5302 | 9.78 | 1100 | 0.7689 |
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+ | 0.5465 | 10.67 | 1200 | 0.7688 |
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+ | 0.5321 | 11.56 | 1300 | 0.7719 |
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+ | 0.5141 | 12.44 | 1400 | 0.7684 |
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+ | 0.5033 | 13.33 | 1500 | 0.7716 |
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+ | 0.4931 | 14.22 | 1600 | 0.7664 |
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+ | 0.4882 | 15.11 | 1700 | 0.7739 |
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+ | 0.4742 | 16.0 | 1800 | 0.7757 |
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+ | 0.4701 | 16.89 | 1900 | 0.7717 |
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+ | 0.4932 | 17.78 | 2000 | 0.7748 |
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+ | 0.4665 | 18.67 | 2100 | 0.7734 |
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+ | 0.4614 | 19.56 | 2200 | 0.7809 |
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+ | 0.4669 | 20.44 | 2300 | 0.7793 |
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+ | 0.4635 | 21.33 | 2400 | 0.7750 |
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+ | 0.452 | 22.22 | 2500 | 0.7778 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - PEFT 0.7.2.dev0
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+ - Transformers 4.38.0.dev0
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.16.1
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  - Tokenizers 0.15.0
adapter_config.json CHANGED
@@ -19,9 +19,9 @@
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  "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
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- "fc2",
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  "Wqkv",
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- "fc1"
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  ],
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  "task_type": "CAUSAL_LM",
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  "use_rslora": false
 
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  "rank_pattern": {},
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  "revision": null,
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  "target_modules": [
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+ "fc1",
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  "Wqkv",
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+ "fc2"
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  ],
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  "task_type": "CAUSAL_LM",
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  "use_rslora": false
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