Deepspeech2 validation WER not decreasing

[HarshalRohit]

Prerequisites

Please answer the following questions for yourself before submitting an issue.

• I am using the latest TensorFlow Model Garden release and TensorFlow 2.
• I am reporting the issue to the correct repository. (Model Garden official or research directory)
• I checked to make sure that this issue has not already been filed.

1. The entire URL of the file you are using

https://github.com/tensorflow/models/tree/master/research/deep_speech

2. Describe the bug

The wer doesn't decrease, it keeps revolving around 1 (from 0.91 to 1.04).
Initially I tried to with train-clean-100 and dev-clean, then
to verify that model is learning I created a very small subset of dev-clean,
which can be found here

Everything else is kept to default values.

3. Steps to reproduce

1. Prepare the dev-clean dataset
2. Change the paths in eval_toy_dataset.csv
3. Change the following line in official/utils/model_helpers.py
if eval_metric >= stop_threshold: to if eval_metric <= stop_threshold:
   Note: The training will stop after first step if this is not modified.
4. execute the training bash file

   toy_dataset="some-prefix/outputs/librispeech_data/eval_dataset_toy.csv"
   
   log_file=same_log_`date +%Y-%m-%d_%H:%M`
   
   nohup python deep_speech.py --train_data_dir=$toy_dataset --eval_data_dir=$toy_dataset --num_gpus=1 \
        --wer_threshold=0.23 --seed=1 --batch_size=16 --train_epochs=30 \
        --model_dir=some-prefix/outputs/same_train_eval \
        --export_dir=some-prefix/outputs/same_train_eval \
        >$log_file 2>&1&
   

**Note: ** flag num_gpus is just to keep other gpus free. batch_size > 16 gives OOM error.

4. Expected behavior

WER should steadily decrease.

5. Additional context

Log for one of the runs - link

6. System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 16.04.7 LTS
• Mobile device name if the issue happens on a mobile device: N/A
• TensorFlow installed from (source or binary): binary
• TensorFlow version (use command below): 2.2
• Python version: 3.8.10
• Bazel version (if compiling from source): N/A
• GCC/Compiler version (if compiling from source):
• CUDA/cuDNN version: 10.2
• GPU model and memory: GeForce GTX 1080 Ti 12GB