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Llama-360M-RUN1

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ninagroot/Llama-360Mtest

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  1. README.md +25 -60
  2. model.safetensors +1 -1
  3. runs/Apr17_14-11-12_gcn25.local.snellius.surf.nl/events.out.tfevents.1713355881.gcn25.local.snellius.surf.nl.3559790.0 +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: 5.6445
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  ## Model description
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@@ -41,71 +41,36 @@ 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: 50
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- - num_epochs: 100
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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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- | 9.595 | 0.57 | 1 | 9.6036 |
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- | 9.4191 | 1.71 | 3 | 9.4004 |
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- | 8.6679 | 2.86 | 5 | 8.9609 |
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- | 7.7889 | 4.0 | 7 | 8.3870 |
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- | 7.4852 | 4.57 | 8 | 8.1495 |
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- | 6.9951 | 5.71 | 10 | 7.7565 |
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- | 6.6337 | 6.86 | 12 | 7.4558 |
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- | 6.2744 | 8.0 | 14 | 7.1806 |
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- | 6.052 | 8.57 | 15 | 7.0535 |
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- | 5.69 | 9.71 | 17 | 6.8455 |
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- | 5.4046 | 10.86 | 19 | 6.6445 |
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- | 5.1682 | 12.0 | 21 | 6.5058 |
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- | 5.0522 | 12.57 | 22 | 6.3872 |
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- | 4.6834 | 13.71 | 24 | 6.2011 |
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- | 4.2821 | 14.86 | 26 | 5.9424 |
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- | 3.9781 | 16.0 | 28 | 5.7461 |
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- | 3.7742 | 16.57 | 29 | 5.6778 |
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- | 3.525 | 17.71 | 31 | 5.5370 |
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- | 3.3434 | 18.86 | 33 | 5.4445 |
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- | 3.0161 | 20.0 | 35 | 5.3650 |
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- | 2.848 | 20.57 | 36 | 5.4065 |
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- | 2.5819 | 21.71 | 38 | 5.3697 |
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- | 2.2761 | 22.86 | 40 | 5.3867 |
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- | 2.0201 | 24.0 | 42 | 5.3975 |
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- | 1.8269 | 24.57 | 43 | 5.4014 |
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- | 1.5501 | 25.71 | 45 | 5.3687 |
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- | 1.3036 | 26.86 | 47 | 5.4212 |
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- | 1.0129 | 28.0 | 49 | 5.4374 |
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- | 0.8856 | 28.57 | 50 | 5.4521 |
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- | 0.6592 | 29.71 | 52 | 5.4968 |
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- | 0.5508 | 30.86 | 54 | 5.4760 |
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- | 0.4567 | 32.0 | 56 | 5.4806 |
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- | 0.4057 | 32.57 | 57 | 5.5026 |
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- | 0.3211 | 33.71 | 59 | 5.5319 |
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- | 0.289 | 34.86 | 61 | 5.5295 |
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- | 0.2501 | 36.0 | 63 | 5.5913 |
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- | 0.2088 | 36.57 | 64 | 5.5563 |
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- | 0.1661 | 37.71 | 66 | 5.5826 |
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- | 0.1405 | 38.86 | 68 | 5.5947 |
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- | 0.1031 | 40.0 | 70 | 5.6525 |
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- | 0.0882 | 40.57 | 71 | 5.6373 |
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- | 0.0609 | 41.71 | 73 | 5.6135 |
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- | 0.0544 | 42.86 | 75 | 5.6294 |
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- | 0.0415 | 44.0 | 77 | 5.6271 |
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- | 0.0358 | 44.57 | 78 | 5.6269 |
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- | 0.0284 | 45.71 | 80 | 5.6244 |
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- | 0.0241 | 46.86 | 82 | 5.6265 |
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- | 0.0207 | 48.0 | 84 | 5.6290 |
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- | 0.0201 | 48.57 | 85 | 5.6310 |
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- | 0.0194 | 49.71 | 87 | 5.6346 |
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- | 0.0182 | 50.86 | 89 | 5.6376 |
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- | 0.0166 | 52.0 | 91 | 5.6402 |
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- | 0.0159 | 52.57 | 92 | 5.6413 |
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- | 0.0156 | 53.71 | 94 | 5.6430 |
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- | 0.0151 | 54.86 | 96 | 5.6440 |
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- | 0.0151 | 56.0 | 98 | 5.6444 |
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- | 0.0151 | 56.57 | 99 | 5.6445 |
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- | 0.0144 | 57.14 | 100 | 5.6445 |
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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: 5.3269
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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: 50
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+ - num_epochs: 40
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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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+ | 9.6295 | 0.57 | 1 | 9.6320 |
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+ | 9.4685 | 1.71 | 3 | 9.4277 |
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+ | 8.7308 | 2.86 | 5 | 8.9834 |
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+ | 7.7978 | 4.0 | 7 | 8.3652 |
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+ | 7.4895 | 4.57 | 8 | 8.1048 |
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+ | 6.9772 | 5.71 | 10 | 7.7260 |
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+ | 6.6117 | 6.86 | 12 | 7.4107 |
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+ | 6.2461 | 8.0 | 14 | 7.1384 |
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+ | 6.0376 | 8.57 | 15 | 6.9993 |
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+ | 5.6415 | 9.71 | 17 | 6.7886 |
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+ | 5.3502 | 10.86 | 19 | 6.6009 |
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+ | 5.0627 | 12.0 | 21 | 6.4227 |
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+ | 4.9292 | 12.57 | 22 | 6.3169 |
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+ | 4.5619 | 13.71 | 24 | 6.1217 |
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+ | 4.1745 | 14.86 | 26 | 5.9089 |
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+ | 3.895 | 16.0 | 28 | 5.7244 |
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+ | 3.7108 | 16.57 | 29 | 5.6837 |
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+ | 3.4811 | 17.71 | 31 | 5.5533 |
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+ | 3.3174 | 18.86 | 33 | 5.4525 |
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+ | 3.0011 | 20.0 | 35 | 5.4535 |
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+ | 2.8812 | 20.57 | 36 | 5.4168 |
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+ | 2.6512 | 21.71 | 38 | 5.4168 |
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+ | 2.3009 | 22.86 | 40 | 5.3269 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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