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NowaBwagel0
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llama-68m-finetuned-wikitext2

Text Generation
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llama
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text-generation-inference
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End of training

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  1. README.md +18 -6
  2. model.safetensors +1 -1
  3. runs/Jan01_17-58-54_ad169494b3b2/events.out.tfevents.1704131940.ad169494b3b2.942.3 +2 -2
  4. runs/Jan01_17-58-54_ad169494b3b2/events.out.tfevents.1704136101.ad169494b3b2.942.4 +3 -0
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [JackFram/llama-68m](https://huggingface.co/JackFram/llama-68m) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.0545
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  ## Model description
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@@ -34,21 +34,33 @@ 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: 32
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  - eval_batch_size: 32
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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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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 175 | 3.0891 |
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- | No log | 2.0 | 350 | 3.0605 |
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- | 3.0721 | 3.0 | 525 | 3.0545 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [JackFram/llama-68m](https://huggingface.co/JackFram/llama-68m) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 5.9290
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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: 0.0003
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  - train_batch_size: 32
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  - eval_batch_size: 32
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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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+ - 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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+ | No log | 1.0 | 175 | 3.1817 |
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+ | No log | 2.0 | 350 | 3.2699 |
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+ | 2.5169 | 3.0 | 525 | 3.4555 |
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+ | 2.5169 | 4.0 | 700 | 3.6923 |
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+ | 2.5169 | 5.0 | 875 | 3.9542 |
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+ | 1.5624 | 6.0 | 1050 | 4.2089 |
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+ | 1.5624 | 7.0 | 1225 | 4.4777 |
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+ | 1.5624 | 8.0 | 1400 | 4.7426 |
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+ | 0.841 | 9.0 | 1575 | 4.9898 |
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+ | 0.841 | 10.0 | 1750 | 5.2385 |
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+ | 0.841 | 11.0 | 1925 | 5.4648 |
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+ | 0.3788 | 12.0 | 2100 | 5.6607 |
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+ | 0.3788 | 13.0 | 2275 | 5.8074 |
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+ | 0.3788 | 14.0 | 2450 | 5.8933 |
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+ | 0.1474 | 15.0 | 2625 | 5.9290 |
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  ### Framework versions
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