End of training

README.md

@@ -1,4 +1,6 @@
 ---
+language:
+- en
 license: apache-2.0
 tags:
 - generated_from_trainer
@@ -13,7 +15,7 @@ model-index:
       name: Text Classification
       type: text-classification
     dataset:
-      name: glue
+      name: GLUE RTE
       type: glue
       config: rte
       split: validation
@@ -21,7 +23,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.51985559566787
+      value: 0.5270758122743683
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,10 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # mobilebert_sa_GLUE_Experiment_rte_128
 
-This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the glue dataset.
+This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) on the GLUE RTE dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6929
-- Accuracy: 0.5199
+- Loss: 0.6926
+- Accuracy: 0.5271
 
 ## Model description
 

all_results.json

@@ -0,0 +1,14 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5270758122743683,
+    "eval_loss": 0.6926150321960449,
+    "eval_runtime": 0.6469,
+    "eval_samples": 277,
+    "eval_samples_per_second": 428.178,
+    "eval_steps_per_second": 4.637,
+    "train_loss": 0.6930288791656494,
+    "train_runtime": 153.3083,
+    "train_samples": 2490,
+    "train_samples_per_second": 812.089,
+    "train_steps_per_second": 6.523
+}

eval_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5270758122743683,
+    "eval_loss": 0.6926150321960449,
+    "eval_runtime": 0.6469,
+    "eval_samples": 277,
+    "eval_samples_per_second": 428.178,
+    "eval_steps_per_second": 4.637
+}

logs/events.out.tfevents.1674681671.garda.227848.14

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ea48c5a9a6d0d5a828c10b0e3f7445e16c2895dd6fd4f6ffe87743da56a20b1b
+size 357

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 6.0,
+    "train_loss": 0.6930288791656494,
+    "train_runtime": 153.3083,
+    "train_samples": 2490,
+    "train_samples_per_second": 812.089,
+    "train_steps_per_second": 6.523
+}

trainer_state.json

@@ -0,0 +1,115 @@
+{
+  "best_metric": 0.6926150321960449,
+  "best_model_checkpoint": "mobilebert_sa_GLUE_Experiment_rte_128/checkpoint-20",
+  "epoch": 6.0,
+  "global_step": 120,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 1.0,
+      "learning_rate": 4.9e-05,
+      "loss": 0.6935,
+      "step": 20
+    },
+    {
+      "epoch": 1.0,
+      "eval_accuracy": 0.5270758122743683,
+      "eval_loss": 0.6926150321960449,
+      "eval_runtime": 0.6362,
+      "eval_samples_per_second": 435.421,
+      "eval_steps_per_second": 4.716,
+      "step": 20
+    },
+    {
+      "epoch": 2.0,
+      "learning_rate": 4.8e-05,
+      "loss": 0.6934,
+      "step": 40
+    },
+    {
+      "epoch": 2.0,
+      "eval_accuracy": 0.5270758122743683,
+      "eval_loss": 0.6930063366889954,
+      "eval_runtime": 0.6364,
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+      "eval_steps_per_second": 4.714,
+      "step": 40
+    },
+    {
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+      "learning_rate": 4.7e-05,
+      "loss": 0.6931,
+      "step": 60
+    },
+    {
+      "epoch": 3.0,
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+      "eval_loss": 0.6932486891746521,
+      "eval_runtime": 0.6297,
+      "eval_samples_per_second": 439.893,
+      "eval_steps_per_second": 4.764,
+      "step": 60
+    },
+    {
+      "epoch": 4.0,
+      "learning_rate": 4.600000000000001e-05,
+      "loss": 0.6932,
+      "step": 80
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+    {
+      "epoch": 4.0,
+      "eval_accuracy": 0.5342960288808665,
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+      "eval_runtime": 0.635,
+      "eval_samples_per_second": 436.245,
+      "eval_steps_per_second": 4.725,
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+    {
+      "epoch": 5.0,
+      "learning_rate": 4.5e-05,
+      "loss": 0.6929,
+      "step": 100
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+    {
+      "epoch": 5.0,
+      "eval_accuracy": 0.4729241877256318,
+      "eval_loss": 0.6944915056228638,
+      "eval_runtime": 0.6203,
+      "eval_samples_per_second": 446.572,
+      "eval_steps_per_second": 4.837,
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+    {
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+      "learning_rate": 4.4000000000000006e-05,
+      "loss": 0.6921,
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+    {
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+      "eval_accuracy": 0.51985559566787,
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+    {
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+      "total_flos": 356088834686976.0,
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+      "train_samples_per_second": 812.089,
+      "train_steps_per_second": 6.523
+    }
+  ],
+  "max_steps": 1000,
+  "num_train_epochs": 50,
+  "total_flos": 356088834686976.0,
+  "trial_name": null,
+  "trial_params": null
+}