End of training

README.md

@@ -1,199 +1,108 @@
 ---
 library_name: transformers
-tags: []
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: xlsr-a-nomi
+  results: []
 ---
 
-# 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]
+<!-- 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. -->
+
+# xlsr-a-nomi
+
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3688
+- Wer: 0.3324
+
+## 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: 0.0004
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- 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
+- lr_scheduler_warmup_steps: 132
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 4.7382        | 2.2727  | 200  | 2.5107          | 1.0    |
+| 1.3613        | 4.5455  | 400  | 0.3782          | 0.5943 |
+| 0.2498        | 6.8182  | 600  | 0.2562          | 0.4209 |
+| 0.1205        | 9.0909  | 800  | 0.2575          | 0.3548 |
+| 0.0772        | 11.3636 | 1000 | 0.2902          | 0.3432 |
+| 0.0625        | 13.6364 | 1200 | 0.3199          | 0.3458 |
+| 0.0461        | 15.9091 | 1400 | 0.2814          | 0.3351 |
+| 0.0348        | 18.1818 | 1600 | 0.3389          | 0.3396 |
+| 0.0323        | 20.4545 | 1800 | 0.3000          | 0.3423 |
+| 0.0341        | 22.7273 | 2000 | 0.3097          | 0.3342 |
+| 0.0271        | 25.0    | 2200 | 0.3270          | 0.3342 |
+| 0.0236        | 27.2727 | 2400 | 0.3370          | 0.3423 |
+| 0.0245        | 29.5455 | 2600 | 0.3201          | 0.3387 |
+| 0.0143        | 31.8182 | 2800 | 0.3483          | 0.3315 |
+| 0.0183        | 34.0909 | 3000 | 0.3245          | 0.3333 |
+| 0.0149        | 36.3636 | 3200 | 0.3269          | 0.3342 |
+| 0.0128        | 38.6364 | 3400 | 0.3180          | 0.3324 |
+| 0.0121        | 40.9091 | 3600 | 0.3465          | 0.3387 |
+| 0.0145        | 43.1818 | 3800 | 0.3465          | 0.3378 |
+| 0.014         | 45.4545 | 4000 | 0.3181          | 0.3342 |
+| 0.0101        | 47.7273 | 4200 | 0.3438          | 0.3333 |
+| 0.0057        | 50.0    | 4400 | 0.3405          | 0.3387 |
+| 0.0101        | 52.2727 | 4600 | 0.3508          | 0.3396 |
+| 0.0084        | 54.5455 | 4800 | 0.3602          | 0.3360 |
+| 0.0057        | 56.8182 | 5000 | 0.3369          | 0.3378 |
+| 0.0143        | 59.0909 | 5200 | 0.3584          | 0.3387 |
+| 0.0062        | 61.3636 | 5400 | 0.3748          | 0.3360 |
+| 0.0068        | 63.6364 | 5600 | 0.3625          | 0.3369 |
+| 0.006         | 65.9091 | 5800 | 0.3773          | 0.3369 |
+| 0.0059        | 68.1818 | 6000 | 0.3666          | 0.3351 |
+| 0.008         | 70.4545 | 6200 | 0.3597          | 0.3378 |
+| 0.0061        | 72.7273 | 6400 | 0.3703          | 0.3396 |
+| 0.0041        | 75.0    | 6600 | 0.3843          | 0.3387 |
+| 0.0055        | 77.2727 | 6800 | 0.3829          | 0.3360 |
+| 0.0028        | 79.5455 | 7000 | 0.3877          | 0.3378 |
+| 0.0025        | 81.8182 | 7200 | 0.3898          | 0.3333 |
+| 0.0021        | 84.0909 | 7400 | 0.3910          | 0.3342 |
+| 0.0021        | 86.3636 | 7600 | 0.3889          | 0.3360 |
+| 0.0025        | 88.6364 | 7800 | 0.3871          | 0.3342 |
+| 0.0025        | 90.9091 | 8000 | 0.3787          | 0.3333 |
+| 0.0016        | 93.1818 | 8200 | 0.3676          | 0.3307 |
+| 0.0017        | 95.4545 | 8400 | 0.3651          | 0.3307 |
+| 0.0015        | 97.7273 | 8600 | 0.3685          | 0.3324 |
+| 0.0015        | 100.0   | 8800 | 0.3688          | 0.3324 |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:740f18e26e24289a100f0e30b6ce630990e2ccbc74445103b1155d2fb07de5be
+oid sha256:31c84b5450c3f744252370c271ca14ef6ac68f0e8984450ef7caef20664606ab
 size 1261930480

runs/Nov16_07-15-43_ba2756cea9a3/events.out.tfevents.1731741370.ba2756cea9a3.30.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8867bd89221d1b92a9565d4e82464d8fb2ff0c4d713c6eef804a575e435582d5
-size 29965
+oid sha256:3937ef31f5b35a0ef393a751d765ddf7b21ac9044bd462076bc7a4ce3b01cb9d
+size 30319