KasuleTrevor
/

w2v-bert-2.0-ln-afrivoice-10hr-v4

Safetensors

wav2vec2-bert

Generated from Trainer

Model card Files Files and versions Community

KasuleTrevor commited on Aug 21

Commit

23c55eb

•

1 Parent(s): d2b66ac

End of training

Browse files

Files changed (2) hide show

README.md +87 -196
model.safetensors +1 -1

README.md CHANGED Viewed

@@ -1,199 +1,90 @@
 ---
-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
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-ln-afrivoice-10hr-v4
+  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. -->
+# w2v-bert-2.0-ln-afrivoice-10hr-v4
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4715
+- Model Preparation Time: 0.0145
+- Wer: 0.2768
+- Cer: 0.0710
+## 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: 5e-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: cosine
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Model Preparation Time | Wer    | Cer    |
+|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:|
+| 3.6215        | 0.9919  | 61   | 1.2506          | 0.0145                 | 0.9280 | 0.3210 |
+| 0.855         | 2.0     | 123  | 0.7710          | 0.0145                 | 0.4019 | 0.1489 |
+| 0.6812        | 2.9919  | 184  | 0.7971          | 0.0145                 | 0.3731 | 0.1379 |
+| 0.585         | 4.0     | 246  | 0.7619          | 0.0145                 | 0.3567 | 0.1329 |
+| 0.542         | 4.9919  | 307  | 0.8564          | 0.0145                 | 0.3502 | 0.1345 |
+| 0.4828        | 6.0     | 369  | 0.7153          | 0.0145                 | 0.3899 | 0.1572 |
+| 0.4398        | 6.9919  | 430  | 0.7300          | 0.0145                 | 0.3568 | 0.1298 |
+| 0.3804        | 8.0     | 492  | 0.8210          | 0.0145                 | 0.3622 | 0.1358 |
+| 0.35          | 8.9919  | 553  | 0.7800          | 0.0145                 | 0.3536 | 0.1339 |
+| 0.3053        | 10.0    | 615  | 0.7407          | 0.0145                 | 0.3718 | 0.1387 |
+| 0.2882        | 10.9919 | 676  | 0.8678          | 0.0145                 | 0.3595 | 0.1370 |
+| 0.2437        | 12.0    | 738  | 0.8548          | 0.0145                 | 0.3744 | 0.1371 |
+| 0.2283        | 12.9919 | 799  | 0.9142          | 0.0145                 | 0.3768 | 0.1391 |
+| 0.1932        | 14.0    | 861  | 1.1226          | 0.0145                 | 0.3585 | 0.1348 |
+| 0.1719        | 14.9919 | 922  | 1.2449          | 0.0145                 | 0.3435 | 0.1293 |
+| 0.1511        | 16.0    | 984  | 1.2415          | 0.0145                 | 0.3693 | 0.1347 |
+| 0.1496        | 16.9919 | 1045 | 1.0652          | 0.0145                 | 0.3738 | 0.1422 |
+| 0.1119        | 18.0    | 1107 | 1.1335          | 0.0145                 | 0.3818 | 0.1416 |
+| 0.0904        | 18.9919 | 1168 | 1.3077          | 0.0145                 | 0.3608 | 0.1346 |
+| 0.0583        | 20.0    | 1230 | 1.5964          | 0.0145                 | 0.3537 | 0.1303 |
+| 0.0454        | 20.9919 | 1291 | 1.4444          | 0.0145                 | 0.3831 | 0.1393 |
+| 0.0349        | 22.0    | 1353 | 1.6557          | 0.0145                 | 0.3663 | 0.1334 |
+| 0.0265        | 22.9919 | 1414 | 1.7123          | 0.0145                 | 0.3540 | 0.1301 |
+| 0.0171        | 24.0    | 1476 | 1.6974          | 0.0145                 | 0.3680 | 0.1353 |
+| 0.0148        | 24.9919 | 1537 | 1.9526          | 0.0145                 | 0.3568 | 0.1309 |
+### Framework versions
+- Transformers 4.44.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e7f33dd623d59db0e3056a38d76360d784502eff4084a3ed555d22975a9f7bf2
 size 2422941660

 version https://git-lfs.github.com/spec/v1
+oid sha256:b1bed10e7a3656c520abb1badbeafe984f11f0d55d7eebbf3778abbba2ecc0d4
 size 2422941660