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ridassaf/operons_t5_base_conservation_gc_func

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Files changed (9) hide show
  1. README.md +22 -7
  2. adapter_config.json +1 -1
  3. adapter_model.safetensors +2 -2
  4. runs/Nov24_06-31-48_3dcee8bb9197/events.out.tfevents.1732429922.3dcee8bb9197.1329.0 +3 -0
  5. runs/Nov24_06-35-52_3dcee8bb9197/events.out.tfevents.1732430158.3dcee8bb9197.4280.0 +3 -0
  6. runs/Nov24_06-38-32_3dcee8bb9197/events.out.tfevents.1732430322.3dcee8bb9197.5182.0 +3 -0
  7. runs/Nov24_06-48-11_3dcee8bb9197/events.out.tfevents.1732430895.3dcee8bb9197.7827.0 +3 -0
  8. runs/Nov24_06-48-23_3dcee8bb9197/events.out.tfevents.1732430907.3dcee8bb9197.7827.1 +3 -0
  9. training_args.bin +1 -1
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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- library_name: transformers
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  license: apache-2.0
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- base_model: google/flan-t5-large
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -14,7 +14,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # t5_large_no_prompt
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- This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
 
 
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  ## Model description
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@@ -34,16 +36,29 @@ More information needed
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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: 16
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- - eval_batch_size: 16
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  - seed: 0
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine_with_restarts
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- - num_epochs: 3
 
 
 
 
 
 
 
 
 
 
 
 
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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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  ---
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+ library_name: peft
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  license: apache-2.0
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+ base_model: google/flan-t5-base
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # t5_large_no_prompt
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+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5291
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  ## Model description
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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: 0
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine_with_restarts
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+ - num_epochs: 6
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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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+ | No log | 1.0 | 70 | 21.6375 |
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+ | No log | 2.0 | 140 | 4.1224 |
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+ | No log | 3.0 | 210 | 1.7503 |
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+ | No log | 4.0 | 280 | 0.7655 |
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+ | No log | 5.0 | 350 | 0.5518 |
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+ | No log | 6.0 | 420 | 0.5291 |
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+
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  ### Framework versions
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+ - PEFT 0.13.2
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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
adapter_config.json CHANGED
@@ -1,7 +1,7 @@
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  "bias": "none",
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  "fan_in_fan_out": false,
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  "inference_mode": true,
 
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  "bias": "none",
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