koshirowada commited on
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Initial model upload

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README.md CHANGED
@@ -7,8 +7,6 @@ tags:
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  model-index:
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  - name: pythia_160m_sft
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  results: []
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- datasets:
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- - tatsu-lab/alpaca_farm
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.1033
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  ## Model description
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@@ -37,7 +35,7 @@ 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: 2e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -50,39 +48,39 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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- | 2.3332 | 0.0889 | 100 | 2.2776 |
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- | 2.3071 | 0.1778 | 200 | 2.2564 |
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- | 2.2941 | 0.2667 | 300 | 2.2301 |
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- | 2.2548 | 0.3556 | 400 | 2.2094 |
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- | 2.2246 | 0.4444 | 500 | 2.1973 |
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- | 2.2189 | 0.5333 | 600 | 2.1705 |
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- | 2.181 | 0.6222 | 700 | 2.1498 |
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- | 2.1515 | 0.7111 | 800 | 2.1399 |
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- | 2.1333 | 0.8 | 900 | 2.1212 |
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- | 2.1139 | 0.8889 | 1000 | 2.1050 |
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- | 2.0778 | 0.9778 | 1100 | 2.0970 |
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- | 1.8312 | 1.0667 | 1200 | 2.1071 |
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- | 1.7405 | 1.1556 | 1300 | 2.1022 |
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- | 1.7284 | 1.2444 | 1400 | 2.1049 |
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- | 1.7554 | 1.3333 | 1500 | 2.1023 |
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- | 1.732 | 1.4222 | 1600 | 2.0934 |
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- | 1.7474 | 1.5111 | 1700 | 2.0917 |
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- | 1.7495 | 1.6 | 1800 | 2.0820 |
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- | 1.7449 | 1.6889 | 1900 | 2.0770 |
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- | 1.7474 | 1.7778 | 2000 | 2.0708 |
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- | 1.7447 | 1.8667 | 2100 | 2.0643 |
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- | 1.7138 | 1.9556 | 2200 | 2.0550 |
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- | 1.5662 | 2.0444 | 2300 | 2.1122 |
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- | 1.4506 | 2.1333 | 2400 | 2.1203 |
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- | 1.4282 | 2.2222 | 2500 | 2.1225 |
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- | 1.4302 | 2.3111 | 2600 | 2.1173 |
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- | 1.4471 | 2.4 | 2700 | 2.1156 |
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- | 1.4217 | 2.4889 | 2800 | 2.1168 |
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- | 1.428 | 2.5778 | 2900 | 2.1126 |
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- | 1.4206 | 2.6667 | 3000 | 2.1059 |
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- | 1.4315 | 2.7556 | 3100 | 2.1068 |
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- | 1.4345 | 2.8444 | 3200 | 2.1037 |
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- | 1.4034 | 2.9333 | 3300 | 2.1033 |
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  ### Framework versions
@@ -90,4 +88,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.46.2
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  - Pytorch 2.5.1+cu121
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  - Datasets 3.1.0
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- - Tokenizers 0.20.3
 
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  model-index:
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  - name: pythia_160m_sft
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  results: []
 
 
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  ---
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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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  This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9831
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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: 2e-06
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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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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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+ | 2.2935 | 0.0889 | 100 | 2.1426 |
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+ | 2.153 | 0.1778 | 200 | 2.0977 |
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+ | 2.1432 | 0.2667 | 300 | 2.0771 |
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+ | 2.1131 | 0.3556 | 400 | 2.0633 |
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+ | 2.0885 | 0.4444 | 500 | 2.0510 |
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+ | 2.0956 | 0.5333 | 600 | 2.0403 |
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+ | 2.0647 | 0.6222 | 700 | 2.0354 |
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+ | 2.0498 | 0.7111 | 800 | 2.0273 |
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+ | 2.0317 | 0.8 | 900 | 2.0202 |
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+ | 2.0226 | 0.8889 | 1000 | 2.0150 |
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+ | 1.992 | 0.9778 | 1100 | 2.0114 |
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+ | 1.9639 | 1.0667 | 1200 | 2.0088 |
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+ | 1.9302 | 1.1556 | 1300 | 2.0051 |
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+ | 1.9381 | 1.2444 | 1400 | 2.0028 |
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+ | 1.9595 | 1.3333 | 1500 | 2.0009 |
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+ | 1.9325 | 1.4222 | 1600 | 1.9998 |
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+ | 1.9481 | 1.5111 | 1700 | 1.9981 |
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+ | 1.9572 | 1.6 | 1800 | 1.9956 |
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+ | 1.9456 | 1.6889 | 1900 | 1.9944 |
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+ | 1.9565 | 1.7778 | 2000 | 1.9922 |
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+ | 1.9507 | 1.8667 | 2100 | 1.9905 |
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+ | 1.9247 | 1.9556 | 2200 | 1.9881 |
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+ | 1.8998 | 2.0444 | 2300 | 1.9874 |
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+ | 1.9102 | 2.1333 | 2400 | 1.9873 |
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+ | 1.8842 | 2.2222 | 2500 | 1.9876 |
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+ | 1.876 | 2.3111 | 2600 | 1.9863 |
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+ | 1.9001 | 2.4 | 2700 | 1.9856 |
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+ | 1.8725 | 2.4889 | 2800 | 1.9859 |
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+ | 1.868 | 2.5778 | 2900 | 1.9845 |
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+ | 1.8803 | 2.6667 | 3000 | 1.9844 |
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+ | 1.9002 | 2.7556 | 3100 | 1.9838 |
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+ | 1.8941 | 2.8444 | 3200 | 1.9839 |
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+ | 1.8548 | 2.9333 | 3300 | 1.9831 |
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  ### Framework versions
 
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  - Transformers 4.46.2
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  - Pytorch 2.5.1+cu121
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  - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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