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: 0.5126353790613718
+      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_256
 
-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: 0.6942
-- Accuracy: 0.5126
+- Loss: 0.6927
+- Accuracy: 0.5271
 
 ## Model description
 

all_results.json

@@ -0,0 +1,14 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5270758122743683,
+    "eval_loss": 0.6926687955856323,
+    "eval_runtime": 0.6714,
+    "eval_samples": 277,
+    "eval_samples_per_second": 412.557,
+    "eval_steps_per_second": 4.468,
+    "train_loss": 0.6928122917811076,
+    "train_runtime": 181.0273,
+    "train_samples": 2490,
+    "train_samples_per_second": 687.741,
+    "train_steps_per_second": 5.524
+}

eval_results.json

@@ -0,0 +1,9 @@
+{
+    "epoch": 6.0,
+    "eval_accuracy": 0.5270758122743683,
+    "eval_loss": 0.6926687955856323,
+    "eval_runtime": 0.6714,
+    "eval_samples": 277,
+    "eval_samples_per_second": 412.557,
+    "eval_steps_per_second": 4.468
+}

logs/events.out.tfevents.1674660604.garda.1292005.14

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9973edf0d9fafaea7ff5a78ad925d58228f399eff7f254d7b18704e5d06e2030
+size 357

train_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 6.0,
+    "train_loss": 0.6928122917811076,
+    "train_runtime": 181.0273,
+    "train_samples": 2490,
+    "train_samples_per_second": 687.741,
+    "train_steps_per_second": 5.524
+}

trainer_state.json

@@ -0,0 +1,115 @@
+{
+  "best_metric": 0.6926687955856323,
+  "best_model_checkpoint": "mobilebert_sa_GLUE_Experiment_rte_256/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": 0.6937,
+      "step": 20
+    },
+    {
+      "epoch": 1.0,
+      "eval_accuracy": 0.5270758122743683,
+      "eval_loss": 0.6926687955856323,
+      "eval_runtime": 0.6537,
+      "eval_samples_per_second": 423.726,
+      "eval_steps_per_second": 4.589,
+      "step": 20
+    },
+    {
+      "epoch": 2.0,
+      "learning_rate": 4.8e-05,
+      "loss": 0.6936,
+      "step": 40
+    },
+    {
+      "epoch": 2.0,
+      "eval_accuracy": 0.5306859205776173,
+      "eval_loss": 0.6928806304931641,
+      "eval_runtime": 0.6521,
+      "eval_samples_per_second": 424.806,
+      "eval_steps_per_second": 4.601,
+      "step": 40
+    },
+    {
+      "epoch": 3.0,
+      "learning_rate": 4.7e-05,
+      "loss": 0.693,
+      "step": 60
+    },
+    {
+      "epoch": 3.0,
+      "eval_accuracy": 0.5018050541516246,
+      "eval_loss": 0.693047285079956,
+      "eval_runtime": 0.6509,
+      "eval_samples_per_second": 425.563,
+      "eval_steps_per_second": 4.609,
+      "step": 60
+    },
+    {
+      "epoch": 4.0,
+      "learning_rate": 4.600000000000001e-05,
+      "loss": 0.693,
+      "step": 80
+    },
+    {
+      "epoch": 4.0,
+      "eval_accuracy": 0.48736462093862815,
+      "eval_loss": 0.693395733833313,
+      "eval_runtime": 0.6512,
+      "eval_samples_per_second": 425.381,
+      "eval_steps_per_second": 4.607,
+      "step": 80
+    },
+    {
+      "epoch": 5.0,
+      "learning_rate": 4.5e-05,
+      "loss": 0.6927,
+      "step": 100
+    },
+    {
+      "epoch": 5.0,
+      "eval_accuracy": 0.4584837545126354,
+      "eval_loss": 0.6946930885314941,
+      "eval_runtime": 0.65,
+      "eval_samples_per_second": 426.135,
+      "eval_steps_per_second": 4.615,
+      "step": 100
+    },
+    {
+      "epoch": 6.0,
+      "learning_rate": 4.4000000000000006e-05,
+      "loss": 0.6909,
+      "step": 120
+    },
+    {
+      "epoch": 6.0,
+      "eval_accuracy": 0.5126353790613718,
+      "eval_loss": 0.6941628456115723,
+      "eval_runtime": 0.6493,
+      "eval_samples_per_second": 426.604,
+      "eval_steps_per_second": 4.62,
+      "step": 120
+    },
+    {
+      "epoch": 6.0,
+      "step": 120,
+      "total_flos": 393536788758528.0,
+      "train_loss": 0.6928122917811076,
+      "train_runtime": 181.0273,
+      "train_samples_per_second": 687.741,
+      "train_steps_per_second": 5.524
+    }
+  ],
+  "max_steps": 1000,
+  "num_train_epochs": 50,
+  "total_flos": 393536788758528.0,
+  "trial_name": null,
+  "trial_params": null
+}