Batch Size and Gradient Accumulation
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Batch Size and Gradient Accumulation has 8 facts recorded in Dontopedia across 2 references, with 3 live disagreements.
Mostly:has component(2), rdf:type(2), has member(2)
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- Strategies for Cpu Fine Tuning
ex:strategies-for-CPU-fine-tuning
Other facts (7)
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| Predicate | Value | Ref |
|---|---|---|
| Has Component | Smaller Batch Sizes | [1] |
| Has Component | Gradient Accumulation | [1] |
| Rdf:type | Optimization Technique | [1] |
| Rdf:type | Related Hyperparameter Pair | [2] |
| Has Member | Batch Size | [2] |
| Has Member | Gradient Accumulation Steps | [2] |
| Is Strategy for | Cpu Fine Tuning | [1] |
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References (2)
ctx:claims/beam/21edf814-3c0d-4bbd-9625-954e304f7ed2- full textbeam-chunktext/plain1 KB
doc:beam/21edf814-3c0d-4bbd-9625-954e304f7ed2Show excerpt
[Turn 2485] Assistant: Certainly! While GPUs significantly speed up the training process, you can still fine-tune the model effectively using CPUs. Here are some strategies to help you manage the fine-tuning process on CPUs: ### Strategies…
ctx:claims/beam/5afb4970-5c3b-4a25-839f-b4f61ca11963- full textbeam-chunktext/plain1 KB
doc:beam/5afb4970-5c3b-4a25-839f-b4f61ca11963Show excerpt
- **Strategy**: Use a learning rate scheduler to adjust the learning rate during training. 2. **Batch Size (`per_device_train_batch_size`)**: - **Description**: Number of samples processed before the model is updated. - **Range**:…
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