End of training

README.md

@@ -15,12 +15,12 @@ should probably proofread and complete it, then remove this comment. -->
 This model was trained from scratch on an unknown dataset.
 It achieves the following results on the evaluation set:
 - eval_loss: 2.2188
-- eval_model_preparation_time: 0.0052
-- eval_cer: 0.4630
-- eval_wer: 0.5242
-- eval_runtime: 46.1107
-- eval_samples_per_second: 12.405
-- eval_steps_per_second: 0.781
+- eval_model_preparation_time: 0.0044
+- eval_cer: 0.3354
+- eval_wer: 0.4724
+- eval_runtime: 43.1274
+- eval_samples_per_second: 13.263
+- eval_steps_per_second: 0.835
 - step: 0
 
 ## Model description

all_results.json

@@ -1,10 +1,10 @@
 {
-    "eval_cer": 0.4629913780505626,
+    "eval_cer": 0.33544957921157537,
     "eval_loss": 2.218759059906006,
-    "eval_model_preparation_time": 0.0052,
-    "eval_runtime": 46.1107,
+    "eval_model_preparation_time": 0.0044,
+    "eval_runtime": 43.1274,
     "eval_samples": 572,
-    "eval_samples_per_second": 12.405,
-    "eval_steps_per_second": 0.781,
-    "eval_wer": 0.5242065233289455
+    "eval_samples_per_second": 13.263,
+    "eval_steps_per_second": 0.835,
+    "eval_wer": 0.47242942811174493
 }

eval_results.json

@@ -1,10 +1,10 @@
 {
-    "eval_cer": 0.4629913780505626,
+    "eval_cer": 0.33544957921157537,
     "eval_loss": 2.218759059906006,
-    "eval_model_preparation_time": 0.0052,
-    "eval_runtime": 46.1107,
+    "eval_model_preparation_time": 0.0044,
+    "eval_runtime": 43.1274,
     "eval_samples": 572,
-    "eval_samples_per_second": 12.405,
-    "eval_steps_per_second": 0.781,
-    "eval_wer": 0.5242065233289455
+    "eval_samples_per_second": 13.263,
+    "eval_steps_per_second": 0.835,
+    "eval_wer": 0.47242942811174493
 }

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fa17cb2655e1bc3e8ad86df389604a3b1d4c89250cbf9ff3e38de4c3ecf760a6
+oid sha256:35cc03612b7f32d98e24dad2241a09f1fb03ab2aef56cadb54287cffb3f8f9c2
 size 5496

transliteratedevalonlyhindi_indicwav2vec_MUCS_warmup500_s300shuff100_3711144.out

@@ -15561,3 +15561,45 @@ Last Prediction string लता द्वारा अनुवादित ह
   eval_steps_per_second       =      0.781
   eval_wer                    =     0.5242
 
+wandb: - 0.011 MB of 0.011 MB uploaded
+wandb: Run history:
+wandb:                    eval/cer ▁
+wandb:                   eval/loss ▁
+wandb: eval/model_preparation_time ▁
+wandb:                eval/runtime ▁
+wandb:     eval/samples_per_second ▁
+wandb:       eval/steps_per_second ▁
+wandb:                    eval/wer ▁
+wandb:                    eval_cer ▁
+wandb:                   eval_loss ▁
+wandb: eval_model_preparation_time ▁
+wandb:                eval_runtime ▁
+wandb:                eval_samples ▁
+wandb:     eval_samples_per_second ▁
+wandb:       eval_steps_per_second ▁
+wandb:                    eval_wer ▁
+wandb:           train/global_step ▁▁
+wandb: 
+wandb: Run summary:
+wandb:                    eval/cer 0.46299
+wandb:                   eval/loss 2.21876
+wandb: eval/model_preparation_time 0.0052
+wandb:                eval/runtime 46.1107
+wandb:     eval/samples_per_second 12.405
+wandb:       eval/steps_per_second 0.781
+wandb:                    eval/wer 0.52421
+wandb:                    eval_cer 0.46299
+wandb:                   eval_loss 2.21876
+wandb: eval_model_preparation_time 0.0052
+wandb:                eval_runtime 46.1107
+wandb:                eval_samples 572
+wandb:     eval_samples_per_second 12.405
+wandb:       eval_steps_per_second 0.781
+wandb:                    eval_wer 0.52421
+wandb:           train/global_step 0
+wandb: 
+wandb: 🚀 View run transliterated_wer_glamorous_tree_37 at: https://wandb.ai/priyanshipal/huggingface/runs/6hswnhgq
+wandb: ⭐️ View project at: https://wandb.ai/priyanshipal/huggingface
+wandb: Synced 6 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
+wandb: Find logs at: ./wandb/run-20241015_002010-6hswnhgq/logs
+wandb: WARNING The new W&B backend becomes opt-out in version 0.18.0; try it out with `wandb.require("core")`! See https://wandb.me/wandb-core for more information.