nbroad HF staff commited on
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1 Parent(s): e68848e

End of training

Browse files
Files changed (5) hide show
  1. README.md +23 -2
  2. all_results.json +6 -6
  3. eval_results.json +3 -3
  4. train_results.json +3 -3
  5. trainer_state.json +12 -12
README.md CHANGED
@@ -3,6 +3,8 @@ license: mit
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  base_model: microsoft/xtremedistil-l6-h256-uncased
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - precision
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  - recall
@@ -10,7 +12,26 @@ metrics:
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  - accuracy
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  model-index:
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  - name: xtremedistil-l6-h256-company-names
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,7 +39,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # xtremedistil-l6-h256-company-names
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- This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0789
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  - Precision: 0.6999
 
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  base_model: microsoft/xtremedistil-l6-h256-uncased
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - nbroad/company_names
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  metrics:
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  - precision
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  - recall
 
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  - accuracy
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  model-index:
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  - name: xtremedistil-l6-h256-company-names
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: nbroad/company_names
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+ type: nbroad/company_names
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.6998602375960866
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+ - name: Recall
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+ type: recall
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+ value: 0.7154210197339048
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+ - name: F1
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+ type: f1
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+ value: 0.7075550845586612
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9702296390871982
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # xtremedistil-l6-h256-company-names
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+ This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased) on the nbroad/company_names dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0789
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  - Precision: 0.6999
all_results.json CHANGED
@@ -5,13 +5,13 @@
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  "eval_loss": 0.07886078208684921,
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  "eval_precision": 0.6998602375960866,
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  "eval_recall": 0.7154210197339048,
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- "eval_runtime": 7.1372,
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  "eval_samples": 14160,
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- "eval_samples_per_second": 1983.973,
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- "eval_steps_per_second": 247.997,
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  "train_loss": 0.11718836608034722,
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- "train_runtime": 82.9226,
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  "train_samples": 102018,
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- "train_samples_per_second": 3690.84,
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- "train_steps_per_second": 76.915
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  }
 
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  "eval_loss": 0.07886078208684921,
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  "eval_precision": 0.6998602375960866,
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  "eval_recall": 0.7154210197339048,
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+ "eval_runtime": 7.0144,
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  "eval_samples": 14160,
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+ "eval_samples_per_second": 2018.718,
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+ "eval_steps_per_second": 252.34,
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  "train_loss": 0.11718836608034722,
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+ "train_runtime": 82.4816,
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  "train_samples": 102018,
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+ "train_samples_per_second": 3710.575,
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+ "train_steps_per_second": 77.326
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  }
eval_results.json CHANGED
@@ -5,8 +5,8 @@
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  "eval_loss": 0.07886078208684921,
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  "eval_precision": 0.6998602375960866,
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  "eval_recall": 0.7154210197339048,
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- "eval_runtime": 7.1372,
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- "eval_samples_per_second": 1983.973,
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- "eval_steps_per_second": 247.997
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  }
 
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  "eval_precision": 0.6998602375960866,
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  "eval_recall": 0.7154210197339048,
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+ "eval_runtime": 7.0144,
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  "eval_samples": 14160,
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+ "eval_samples_per_second": 2018.718,
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+ "eval_steps_per_second": 252.34
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  }
train_results.json CHANGED
@@ -1,8 +1,8 @@
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  {
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  "epoch": 3.0,
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  "train_loss": 0.11718836608034722,
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- "train_runtime": 82.9226,
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- "train_samples_per_second": 3690.84,
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- "train_steps_per_second": 76.915
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  }
 
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  {
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  "epoch": 3.0,
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  "train_loss": 0.11718836608034722,
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+ "train_runtime": 82.4816,
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  "train_samples": 102018,
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+ "train_samples_per_second": 3710.575,
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+ "train_steps_per_second": 77.326
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  }
trainer_state.json CHANGED
@@ -1287,9 +1287,9 @@
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  "step": 2126
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@@ -2577,9 +2577,9 @@
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  {
@@ -3861,9 +3861,9 @@
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@@ -3871,9 +3871,9 @@
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