aguglaniAI commited on
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phi2 fine-tuned with full dataset and high learning rate: Loss dropped to 0.02

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README.md CHANGED
@@ -20,12 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the generator dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 0.2468
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- - eval_runtime: 107.7441
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- - eval_samples_per_second: 4.093
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- - eval_steps_per_second: 0.52
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- - epoch: 8.69
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- - step: 120
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  ## Model description
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@@ -44,7 +39,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0002
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  - train_batch_size: 2
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  - eval_batch_size: 8
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  - seed: 42
@@ -52,14 +47,48 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 32
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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- - lr_scheduler_warmup_ratio: 0.05
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- - lr_scheduler_warmup_steps: 5
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- - training_steps: 250
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - PEFT 0.8.2
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- - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.1
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the generator dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8105
 
 
 
 
 
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0008
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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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  - total_train_batch_size: 32
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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+ - training_steps: 300
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.6408 | 0.72 | 10 | 0.5720 |
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+ | 0.4116 | 1.45 | 20 | 0.5234 |
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+ | 0.3467 | 2.17 | 30 | 0.5068 |
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+ | 0.328 | 2.9 | 40 | 0.4990 |
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+ | 0.3013 | 3.62 | 50 | 0.5022 |
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+ | 0.267 | 4.34 | 60 | 0.5051 |
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+ | 0.2407 | 5.07 | 70 | 0.5151 |
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+ | 0.2084 | 5.79 | 80 | 0.5329 |
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+ | 0.1821 | 6.52 | 90 | 0.5566 |
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+ | 0.1635 | 7.24 | 100 | 0.5996 |
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+ | 0.1431 | 7.96 | 110 | 0.6137 |
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+ | 0.1164 | 8.69 | 120 | 0.6461 |
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+ | 0.1045 | 9.41 | 130 | 0.6714 |
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+ | 0.0903 | 10.14 | 140 | 0.6719 |
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+ | 0.0773 | 10.86 | 150 | 0.6802 |
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+ | 0.0653 | 11.58 | 160 | 0.7234 |
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+ | 0.0595 | 12.31 | 170 | 0.7497 |
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+ | 0.0523 | 13.03 | 180 | 0.7281 |
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+ | 0.0453 | 13.76 | 190 | 0.7439 |
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+ | 0.0405 | 14.48 | 200 | 0.7655 |
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+ | 0.0363 | 15.2 | 210 | 0.7674 |
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+ | 0.0323 | 15.93 | 220 | 0.7835 |
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+ | 0.0293 | 16.65 | 230 | 0.7924 |
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+ | 0.0276 | 17.38 | 240 | 0.7981 |
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+ | 0.0257 | 18.1 | 250 | 0.8023 |
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+ | 0.0252 | 18.82 | 260 | 0.8019 |
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+ | 0.0236 | 19.55 | 270 | 0.8040 |
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+ | 0.023 | 20.27 | 280 | 0.8089 |
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+ | 0.0232 | 21.0 | 290 | 0.8104 |
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+ | 0.0231 | 21.72 | 300 | 0.8105 |
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+
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  ### Framework versions
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+ - PEFT 0.9.0
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+ - Transformers 4.38.1
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.1
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  - Tokenizers 0.15.2
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+ "Wqkv",
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+ "fc2"
 
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  "task_type": "CAUSAL_LM",
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