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satpalsr
/
phi2-filter2

Text Generation
Transformers
PyTorch
Safetensors
phi-msft
axolotl
Generated from Trainer
custom_code
Inference Endpoints
Model card Files Community
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  1. README.md +6 -27
  2. model-00001-of-00002.safetensors +2 -2
  3. model-00002-of-00002.safetensors +2 -2
  4. model.safetensors.index.json +326 -454
  5. pytorch_model-00001-of-00002.bin +2 -2
  6. pytorch_model-00002-of-00002.bin +2 -2
  7. pytorch_model.bin.index.json +326 -454
README.md CHANGED
@@ -18,6 +18,7 @@ should probably proofread and complete it, then remove this comment. -->
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  axolotl version: `0.3.0`
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  ```yaml
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  base_model: microsoft/phi-2
 
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  model_type: AutoModelForCausalLM
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  tokenizer_type: AutoTokenizer
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  trust_remote_code: true
@@ -30,12 +31,12 @@ hub_model_id: satpalsr/phi2-filter2
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  hf_use_auth_token: true
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  datasets:
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- - path: satpalsr/translation-filter
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  type: completion
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  dataset_prepared_path:
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- val_set_size: 0.01
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- output_dir: ./phi-sft-out2
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  sequence_len: 2048
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  sample_packing: false # currently unsupported
@@ -60,7 +61,7 @@ wandb_log_model:
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  gradient_accumulation_steps: 1
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  micro_batch_size: 16
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- num_epochs: 4
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  optimizer: paged_adamw_8bit
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  adam_beta2: 0.95
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  adam_epsilon: 0.00001
@@ -83,7 +84,6 @@ xformers_attention:
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  flash_attention: false
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  warmup_steps: 100
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- evals_per_epoch: 4
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  saves_per_epoch: 1
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  debug:
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  deepspeed:
@@ -100,8 +100,6 @@ special_tokens:
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  # phi2-filter2
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  This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 0.1944
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  ## Model description
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@@ -127,29 +125,10 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 100
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- - num_epochs: 4
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | 2.5676 | 0.01 | 1 | 2.5391 |
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- | 2.4364 | 0.25 | 29 | 2.4042 |
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- | 1.9523 | 0.5 | 58 | 1.8580 |
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- | 1.1137 | 0.75 | 87 | 0.9535 |
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- | 0.5107 | 1.0 | 116 | 0.4195 |
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- | 0.4588 | 1.25 | 145 | 0.2877 |
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- | 0.2876 | 1.5 | 174 | 0.2462 |
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- | 0.2959 | 1.75 | 203 | 0.2264 |
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- | 0.2197 | 2.0 | 232 | 0.2114 |
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- | 0.3045 | 2.25 | 261 | 0.2052 |
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- | 0.2726 | 2.5 | 290 | 0.2022 |
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- | 0.3046 | 2.75 | 319 | 0.1975 |
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- | 0.3316 | 3.0 | 348 | 0.1954 |
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- | 0.2223 | 3.25 | 377 | 0.1950 |
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- | 0.2609 | 3.5 | 406 | 0.1946 |
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- | 0.2739 | 3.75 | 435 | 0.1945 |
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- | 0.2703 | 4.0 | 464 | 0.1944 |
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  ### Framework versions
 
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  axolotl version: `0.3.0`
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  ```yaml
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  base_model: microsoft/phi-2
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+ model_revision: 834565c # pin model repo to the previous architecture
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  model_type: AutoModelForCausalLM
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  tokenizer_type: AutoTokenizer
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  trust_remote_code: true
 
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  hf_use_auth_token: true
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  datasets:
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+ - path: satpalsr/phifilter
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  type: completion
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  dataset_prepared_path:
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+ val_set_size: 0.0
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+ output_dir: ./phi2-filter2
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  sequence_len: 2048
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  sample_packing: false # currently unsupported
 
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  gradient_accumulation_steps: 1
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  micro_batch_size: 16
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+ num_epochs: 16
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  optimizer: paged_adamw_8bit
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  adam_beta2: 0.95
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  adam_epsilon: 0.00001
 
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  flash_attention: false
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  warmup_steps: 100
 
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  saves_per_epoch: 1
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  debug:
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  deepspeed:
 
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  # phi2-filter2
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  This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
 
 
103
 
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  ## Model description
105
 
 
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  - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 16
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  ### Training results
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  ### Framework versions
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331
  }
332
  }