End of training

README.md

@@ -3,9 +3,35 @@ license: apache-2.0
 base_model: bert-base-uncased
 tags:
 - generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: token-classification-bert-base-uncased
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9465865464863963
+    - name: Recall
+      type: recall
+      value: 0.9543924604510265
+    - name: F1
+      type: f1
+      value: 0.9504734769127628
+    - name: Accuracy
+      type: accuracy
+      value: 0.9898757836532845
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -13,7 +39,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # token-classification-bert-base-uncased
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0480
+- Precision: 0.9466
+- Recall: 0.9544
+- F1: 0.9505
+- Accuracy: 0.9899
 
 ## Model description
 

all_results.json

@@ -0,0 +1,17 @@
+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.9898757836532845,
+    "eval_f1": 0.9504734769127628,
+    "eval_loss": 0.04797038435935974,
+    "eval_precision": 0.9465865464863963,
+    "eval_recall": 0.9543924604510265,
+    "eval_runtime": 10.3106,
+    "eval_samples": 3250,
+    "eval_samples_per_second": 315.208,
+    "eval_steps_per_second": 39.474,
+    "train_loss": 0.043311251413668296,
+    "train_runtime": 605.4597,
+    "train_samples": 14041,
+    "train_samples_per_second": 69.572,
+    "train_steps_per_second": 8.701
+}

eval_results.json

@@ -0,0 +1,12 @@
+{
+    "epoch": 3.0,
+    "eval_accuracy": 0.9898757836532845,
+    "eval_f1": 0.9504734769127628,
+    "eval_loss": 0.04797038435935974,
+    "eval_precision": 0.9465865464863963,
+    "eval_recall": 0.9543924604510265,
+    "eval_runtime": 10.3106,
+    "eval_samples": 3250,
+    "eval_samples_per_second": 315.208,
+    "eval_steps_per_second": 39.474
+}

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 3.0,
+    "train_loss": 0.043311251413668296,
+    "train_runtime": 605.4597,
+    "train_samples": 14041,
+    "train_samples_per_second": 69.572,
+    "train_steps_per_second": 8.701
+}

trainer_state.json

@@ -0,0 +1,88 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 3.0,
+  "eval_steps": 500,
+  "global_step": 5268,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "epoch": 0.28,
+      "learning_rate": 4.525436598329537e-05,
+      "loss": 0.154,
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+      "step": 1000
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+    {
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+      "loss": 0.0625,
+      "step": 1500
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+    {
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+      "learning_rate": 3.1017463933181475e-05,
+      "loss": 0.0427,
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+    },
+    {
+      "epoch": 1.42,
+      "learning_rate": 2.6271829916476843e-05,
+      "loss": 0.0245,
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+    },
+    {
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+      "loss": 0.0296,
+      "step": 3000
+    },
+    {
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+      "learning_rate": 1.678056188306758e-05,
+      "loss": 0.0264,
+      "step": 3500
+    },
+    {
+      "epoch": 2.28,
+      "learning_rate": 1.2034927866362947e-05,
+      "loss": 0.0115,
+      "step": 4000
+    },
+    {
+      "epoch": 2.56,
+      "learning_rate": 7.289293849658315e-06,
+      "loss": 0.0108,
+      "step": 4500
+    },
+    {
+      "epoch": 2.85,
+      "learning_rate": 2.5436598329536827e-06,
+      "loss": 0.0103,
+      "step": 5000
+    },
+    {
+      "epoch": 3.0,
+      "step": 5268,
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+      "train_loss": 0.043311251413668296,
+      "train_runtime": 605.4597,
+      "train_samples_per_second": 69.572,
+      "train_steps_per_second": 8.701
+    }
+  ],
+  "logging_steps": 500,
+  "max_steps": 5268,
+  "num_train_epochs": 3,
+  "save_steps": 500,
+  "total_flos": 895156246626660.0,
+  "trial_name": null,
+  "trial_params": null
+}