Sajjo
/

w2v-bert-2.0-bangala-gpu-CV16.0_v2

@@ -1,199 +1,109 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-[More Information Needed]
-### Downstream Use [optional]
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-[More Information Needed]
-### Out-of-Scope Use
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-[More Information Needed]
-## Bias, Risks, and Limitations
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-[More Information Needed]
-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-[More Information Needed]
-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
-[More Information Needed]
-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-[More Information Needed]
-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
-<!-- This should link to a Dataset Card if possible. -->
-[More Information Needed]
-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-[More Information Needed]
-#### Metrics
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-[More Information Needed]
-### Results
-[More Information Needed]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_16_0
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-bangala-gpu-CV16.0_v2
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: bn
+      split: test
+      args: bn
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.4811011116993118
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# w2v-bert-2.0-bangala-gpu-CV16.0_v2
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4490
+- Wer: 0.4811
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 4.42184e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 3.5221        | 0.31  | 300  | 0.5900          | 0.6271 |
+| 1.2024        | 0.63  | 600  | 0.4088          | 0.4071 |
+| 0.9149        | 0.94  | 900  | 0.3200          | 0.3270 |
+| 0.8124        | 1.26  | 1200 | 0.2965          | 0.3080 |
+| 0.7028        | 1.57  | 1500 | 0.2759          | 0.2884 |
+| 0.6301        | 1.89  | 1800 | 0.2435          | 0.2671 |
+| 0.6147        | 2.2   | 2100 | 0.2335          | 0.2477 |
+| 0.6304        | 2.52  | 2400 | 0.2248          | 0.2458 |
+| 0.5921        | 2.83  | 2700 | 0.2326          | 0.2441 |
+| 0.495         | 3.15  | 3000 | 0.2180          | 0.2378 |
+| 0.4987        | 3.46  | 3300 | 0.2139          | 0.2227 |
+| 0.5669        | 3.78  | 3600 | 0.2097          | 0.2236 |
+| 0.5904        | 4.09  | 3900 | 0.2038          | 0.2178 |
+| 0.6016        | 4.41  | 4200 | 0.2091          | 0.2131 |
+| 0.5325        | 4.72  | 4500 | 0.2064          | 0.2147 |
+| 0.5271        | 5.04  | 4800 | 0.2002          | 0.2159 |
+| 0.5229        | 5.35  | 5100 | 0.2069          | 0.2209 |
+| 0.5843        | 5.67  | 5400 | 0.2090          | 0.2202 |
+| 0.5477        | 5.98  | 5700 | 0.2085          | 0.2175 |
+| 0.508         | 6.3   | 6000 | 0.2046          | 0.2158 |
+| 0.5226        | 6.61  | 6300 | 0.2515          | 0.3250 |
+| 0.7576        | 6.93  | 6600 | 0.2343          | 0.2364 |
+| 1.0089        | 7.24  | 6900 | 0.2731          | 0.2713 |
+| 0.9462        | 7.56  | 7200 | 0.2588          | 0.2648 |
+| 0.8648        | 7.87  | 7500 | 0.2916          | 0.3393 |
+| 1.1282        | 8.19  | 7800 | 0.3830          | 0.4583 |
+| 1.3279        | 8.5   | 8100 | 0.3910          | 0.4117 |
+| 1.2722        | 8.82  | 8400 | 0.4424          | 0.3442 |
+| 1.2886        | 9.13  | 8700 | 0.4421          | 0.4011 |
+| 1.3274        | 9.45  | 9000 | 0.4483          | 0.4769 |
+| 1.3235        | 9.76  | 9300 | 0.4490          | 0.4811 |
+### Framework versions
+- Transformers 4.39.3
+- Pytorch 2.1.2+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.0

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:db95c90eb4e3aba1b76b946eef2178133c59384875cbbc710b6be3ae00e85e47
 size 2423126260

 version https://git-lfs.github.com/spec/v1
+oid sha256:a58b3292e0000e6d9a950d5a64af11b0bb2c5cee645c03fb150a46146ad578ff
 size 2423126260

runs/Apr05_22-50-07_GPU/events.out.tfevents.1712337973.GPU.145321.0 CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:df231f5aecc844e246aa046cb9e61367878ee32f3e8511d6ab2f1cf21f98c6cf
-size 21781

 version https://git-lfs.github.com/spec/v1
+oid sha256:b38288d3ed66b56ea5c0bb452a3e8379f8593ea038c9f9d4af9412bd27dd5243
+size 22664