sulaimank
/

wav2vec-xlsr-cv-grain-lg_both

@@ -1,199 +1,163 @@
 ---
 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]

 ---
 library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: wav2vec-xlsr-cv-grain-lg_both
+  results: []
 ---
+<!-- 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. -->
+# wav2vec-xlsr-cv-grain-lg_both
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0871
+- Wer: 0.0289
+- Cer: 0.0079
+## 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: 0.0003
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step   | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
+| 1.9082        | 1.0   | 2703   | 0.2081          | 0.2630 | 0.0539 |
+| 0.6172        | 2.0   | 5406   | 0.1523          | 0.1853 | 0.0386 |
+| 0.5149        | 3.0   | 8109   | 0.1235          | 0.1432 | 0.0307 |
+| 0.4589        | 4.0   | 10812  | 0.1207          | 0.1297 | 0.0285 |
+| 0.4226        | 5.0   | 13515  | 0.1007          | 0.1117 | 0.0238 |
+| 0.3932        | 6.0   | 16218  | 0.0988          | 0.0979 | 0.0225 |
+| 0.3706        | 7.0   | 18921  | 0.0916          | 0.0924 | 0.0212 |
+| 0.3481        | 8.0   | 21624  | 0.0882          | 0.0881 | 0.0210 |
+| 0.3291        | 9.0   | 24327  | 0.0856          | 0.0803 | 0.0185 |
+| 0.3131        | 10.0  | 27030  | 0.0806          | 0.0777 | 0.0182 |
+| 0.2997        | 11.0  | 29733  | 0.0767          | 0.0733 | 0.0175 |
+| 0.2851        | 12.0  | 32436  | 0.0749          | 0.0742 | 0.0178 |
+| 0.2745        | 13.0  | 35139  | 0.0738          | 0.0636 | 0.0161 |
+| 0.2628        | 14.0  | 37842  | 0.0818          | 0.0749 | 0.0177 |
+| 0.2487        | 15.0  | 40545  | 0.0750          | 0.0699 | 0.0162 |
+| 0.2389        | 16.0  | 43248  | 0.0682          | 0.0586 | 0.0145 |
+| 0.2299        | 17.0  | 45951  | 0.0675          | 0.0590 | 0.0137 |
+| 0.22          | 18.0  | 48654  | 0.0715          | 0.0562 | 0.0140 |
+| 0.2102        | 19.0  | 51357  | 0.0757          | 0.0534 | 0.0134 |
+| 0.202         | 20.0  | 54060  | 0.0785          | 0.0586 | 0.0149 |
+| 0.195         | 21.0  | 56763  | 0.0731          | 0.0590 | 0.0136 |
+| 0.186         | 22.0  | 59466  | 0.0750          | 0.0566 | 0.0136 |
+| 0.1797        | 23.0  | 62169  | 0.0746          | 0.0523 | 0.0127 |
+| 0.1713        | 24.0  | 64872  | 0.0739          | 0.0538 | 0.0132 |
+| 0.1634        | 25.0  | 67575  | 0.0806          | 0.0514 | 0.0130 |
+| 0.157         | 26.0  | 70278  | 0.0748          | 0.0532 | 0.0132 |
+| 0.1521        | 27.0  | 72981  | 0.0774          | 0.0521 | 0.0133 |
+| 0.1483        | 28.0  | 75684  | 0.0775          | 0.0501 | 0.0125 |
+| 0.1424        | 29.0  | 78387  | 0.0772          | 0.0479 | 0.0122 |
+| 0.1363        | 30.0  | 81090  | 0.0747          | 0.0453 | 0.0116 |
+| 0.1322        | 31.0  | 83793  | 0.0801          | 0.0436 | 0.0116 |
+| 0.1266        | 32.0  | 86496  | 0.0758          | 0.0473 | 0.0112 |
+| 0.1234        | 33.0  | 89199  | 0.0691          | 0.0430 | 0.0107 |
+| 0.1214        | 34.0  | 91902  | 0.0853          | 0.0458 | 0.0120 |
+| 0.1178        | 35.0  | 94605  | 0.0805          | 0.0436 | 0.0107 |
+| 0.1126        | 36.0  | 97308  | 0.0803          | 0.0436 | 0.0116 |
+| 0.1119        | 37.0  | 100011 | 0.0744          | 0.0412 | 0.0105 |
+| 0.1079        | 38.0  | 102714 | 0.0788          | 0.0421 | 0.0106 |
+| 0.1039        | 39.0  | 105417 | 0.0802          | 0.0406 | 0.0105 |
+| 0.1014        | 40.0  | 108120 | 0.0741          | 0.0367 | 0.0098 |
+| 0.1           | 41.0  | 110823 | 0.0812          | 0.0401 | 0.0106 |
+| 0.096         | 42.0  | 113526 | 0.0772          | 0.0410 | 0.0111 |
+| 0.0937        | 43.0  | 116229 | 0.0782          | 0.0417 | 0.0106 |
+| 0.0923        | 44.0  | 118932 | 0.0808          | 0.0404 | 0.0104 |
+| 0.0894        | 45.0  | 121635 | 0.0725          | 0.0384 | 0.0097 |
+| 0.0874        | 46.0  | 124338 | 0.0747          | 0.0351 | 0.0098 |
+| 0.0856        | 47.0  | 127041 | 0.0761          | 0.0373 | 0.0100 |
+| 0.0852        | 48.0  | 129744 | 0.0786          | 0.0393 | 0.0099 |
+| 0.0821        | 49.0  | 132447 | 0.0766          | 0.0334 | 0.0092 |
+| 0.0815        | 50.0  | 135150 | 0.0789          | 0.0365 | 0.0103 |
+| 0.0798        | 51.0  | 137853 | 0.0813          | 0.0391 | 0.0101 |
+| 0.0775        | 52.0  | 140556 | 0.0783          | 0.0341 | 0.0091 |
+| 0.0755        | 53.0  | 143259 | 0.0793          | 0.0399 | 0.0105 |
+| 0.0745        | 54.0  | 145962 | 0.0770          | 0.0408 | 0.0100 |
+| 0.072         | 55.0  | 148665 | 0.0774          | 0.0349 | 0.0093 |
+| 0.0708        | 56.0  | 151368 | 0.0811          | 0.0341 | 0.0091 |
+| 0.0675        | 57.0  | 154071 | 0.0740          | 0.0321 | 0.0087 |
+| 0.067         | 58.0  | 156774 | 0.0747          | 0.0321 | 0.0087 |
+| 0.0657        | 59.0  | 159477 | 0.0721          | 0.0312 | 0.0085 |
+| 0.0645        | 60.0  | 162180 | 0.0701          | 0.0341 | 0.0089 |
+| 0.0631        | 61.0  | 164883 | 0.0788          | 0.0358 | 0.0090 |
+| 0.0623        | 62.0  | 167586 | 0.0763          | 0.0312 | 0.0091 |
+| 0.0614        | 63.0  | 170289 | 0.0777          | 0.0332 | 0.0087 |
+| 0.0592        | 64.0  | 172992 | 0.0742          | 0.0319 | 0.0085 |
+| 0.0576        | 65.0  | 175695 | 0.0755          | 0.0317 | 0.0085 |
+| 0.0566        | 66.0  | 178398 | 0.0785          | 0.0347 | 0.0092 |
+| 0.0565        | 67.0  | 181101 | 0.0794          | 0.0315 | 0.0086 |
+| 0.0559        | 68.0  | 183804 | 0.0774          | 0.0317 | 0.0084 |
+| 0.0534        | 69.0  | 186507 | 0.0814          | 0.0338 | 0.0088 |
+| 0.0521        | 70.0  | 189210 | 0.0825          | 0.0330 | 0.0089 |
+| 0.0514        | 71.0  | 191913 | 0.0781          | 0.0297 | 0.0081 |
+| 0.0489        | 72.0  | 194616 | 0.0802          | 0.0293 | 0.0079 |
+| 0.0496        | 73.0  | 197319 | 0.0799          | 0.0330 | 0.0086 |
+| 0.0474        | 74.0  | 200022 | 0.0806          | 0.0299 | 0.0080 |
+| 0.0479        | 75.0  | 202725 | 0.0789          | 0.0284 | 0.0080 |
+| 0.0461        | 76.0  | 205428 | 0.0797          | 0.0308 | 0.0079 |
+| 0.044         | 77.0  | 208131 | 0.0788          | 0.0284 | 0.0078 |
+| 0.0444        | 78.0  | 210834 | 0.0830          | 0.0304 | 0.0083 |
+| 0.0429        | 79.0  | 213537 | 0.0826          | 0.0312 | 0.0085 |
+| 0.0423        | 80.0  | 216240 | 0.0845          | 0.0317 | 0.0087 |
+| 0.041         | 81.0  | 218943 | 0.0862          | 0.0323 | 0.0085 |
+| 0.0399        | 82.0  | 221646 | 0.0844          | 0.0297 | 0.0083 |
+| 0.0402        | 83.0  | 224349 | 0.0884          | 0.0308 | 0.0084 |
+| 0.0389        | 84.0  | 227052 | 0.0853          | 0.0276 | 0.0079 |
+| 0.0372        | 85.0  | 229755 | 0.0839          | 0.0325 | 0.0082 |
+| 0.0367        | 86.0  | 232458 | 0.0851          | 0.0282 | 0.0078 |
+| 0.0358        | 87.0  | 235161 | 0.0836          | 0.0297 | 0.0081 |
+| 0.0355        | 88.0  | 237864 | 0.0860          | 0.0295 | 0.0083 |
+| 0.0347        | 89.0  | 240567 | 0.0848          | 0.0291 | 0.0081 |
+| 0.0334        | 90.0  | 243270 | 0.0832          | 0.0280 | 0.0079 |
+| 0.033         | 91.0  | 245973 | 0.0848          | 0.0282 | 0.0079 |
+| 0.0329        | 92.0  | 248676 | 0.0852          | 0.0286 | 0.0082 |
+| 0.0317        | 93.0  | 251379 | 0.0851          | 0.0291 | 0.0080 |
+| 0.0314        | 94.0  | 254082 | 0.0873          | 0.0291 | 0.0080 |
+| 0.0313        | 95.0  | 256785 | 0.0869          | 0.0284 | 0.0079 |
+| 0.0305        | 96.0  | 259488 | 0.0853          | 0.0291 | 0.0080 |
+| 0.03          | 97.0  | 262191 | 0.0862          | 0.0280 | 0.0077 |
+| 0.0299        | 98.0  | 264894 | 0.0865          | 0.0282 | 0.0078 |
+| 0.0286        | 99.0  | 267597 | 0.0871          | 0.0289 | 0.0079 |
+### Framework versions
+- Transformers 4.46.1
+- Pytorch 2.1.0+cu118
+- Datasets 3.1.0
+- Tokenizers 0.20.1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5c64d5831f5e55c8030fa148dbd6023492a61cf890d78105c919d0e3294168c4
 size 1261967380

 version https://git-lfs.github.com/spec/v1
+oid sha256:fc11d10e88792043460e44403c58da46101a97ee232dc62e5afbdc1ac177b3ba
 size 1261967380