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Llama-360M-RUN1

Text Generation
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ninagroot/Llama-360Mtest

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  1. README.md +20 -6
  2. model.safetensors +1 -1
  3. runs/Mar20_14-33-09_gcn44.local.snellius.surf.nl/events.out.tfevents.1710941597.gcn44.local.snellius.surf.nl.624542.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -13,7 +13,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 8.2764
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  ## Model description
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@@ -41,17 +41,31 @@ The following hyperparameters were used during training:
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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_steps: 300
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- - num_epochs: 4
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  - mixed_precision_training: Native AMP
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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 | 0.89 | 2 | 8.5545 |
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- | No log | 1.78 | 4 | 8.5018 |
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- | No log | 2.67 | 6 | 8.4091 |
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- | No log | 3.56 | 8 | 8.2764 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 5.9655
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  ## Model description
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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_steps: 300
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+ - num_epochs: 20
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  - mixed_precision_training: Native AMP
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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 | 0.89 | 2 | 8.5679 |
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+ | No log | 1.78 | 4 | 8.5182 |
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+ | No log | 2.67 | 6 | 8.4304 |
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+ | No log | 4.0 | 9 | 8.2278 |
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+ | No log | 4.89 | 11 | 8.0473 |
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+ | No log | 5.78 | 13 | 7.8459 |
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+ | No log | 6.67 | 15 | 7.6372 |
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+ | No log | 8.0 | 18 | 7.3787 |
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+ | 7.9918 | 8.89 | 20 | 7.1956 |
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+ | 7.9918 | 9.78 | 22 | 7.0644 |
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+ | 7.9918 | 10.67 | 24 | 6.9150 |
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+ | 7.9918 | 12.0 | 27 | 6.7280 |
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+ | 7.9918 | 12.89 | 29 | 6.5960 |
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+ | 7.9918 | 13.78 | 31 | 6.4792 |
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+ | 7.9918 | 14.67 | 33 | 6.3487 |
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+ | 7.9918 | 16.0 | 36 | 6.1616 |
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+ | 7.9918 | 16.89 | 38 | 6.0606 |
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+ | 6.3677 | 17.78 | 40 | 5.9655 |
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  ### Framework versions
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